{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 空间数据的选择和存取"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. 使用`read_file()`函数打开矢量数据，自定义`CSV`格式的空间数据的加载\n",
    "2. 掌握根据属性信息和几何信息两种空间数据的方法，学会用于`GeoDataFrame`和`DataFrame`数据的遍历的`apply()`函数；\n",
    "3. 了解和学会判断几何对象间关系的函数，如`contain()，intersects()，within()`等的使用方法；\n",
    "4. 掌握存储空间数据`to_file()`函数的使用方法。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 打开矢量数据\n",
    "> `Geopandas`本身支持很多种矢量数据的格式，如：`ESRI shp，geojson，gpkg，postgis`等，这些格式的数据都可以使用`Geopandas`直接打开"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import geopandas as gpd\n",
    "from shapely.geometry import Point\n",
    "import pandas as pd\n",
    "from sqlalchemy import create_engine"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1. 打开`shp`文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>descriptio</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>begin</th>\n",
       "      <th>end</th>\n",
       "      <th>altitudeMo</th>\n",
       "      <th>tessellate</th>\n",
       "      <th>extrude</th>\n",
       "      <th>visibility</th>\n",
       "      <th>drawOrder</th>\n",
       "      <th>icon</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>-1</td>\n",
       "      <td>0</td>\n",
       "      <td>-1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((104.02373 30.78543, 104.08913 30.791...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Name descriptio timestamp begin   end altitudeMo  tessellate  extrude  \\\n",
       "0  None       None      None  None  None       None          -1        0   \n",
       "\n",
       "   visibility drawOrder  icon  \\\n",
       "0          -1      None  None   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((104.02373 30.78543, 104.08913 30.791...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1. 简单打开\n",
    "polylayer = gpd.read_file('./data/cdbd.shp')\n",
    "polylayer.plot()\n",
    "plt.show()\n",
    "polylayer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>osm_id</th>\n",
       "      <th>name</th>\n",
       "      <th>barrier</th>\n",
       "      <th>highway</th>\n",
       "      <th>ref</th>\n",
       "      <th>address</th>\n",
       "      <th>is_in</th>\n",
       "      <th>place</th>\n",
       "      <th>man_made</th>\n",
       "      <th>other_tags</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>244077729</td>\n",
       "      <td>成都市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"admin_level\"=&gt;\"4\",\"capital\"=&gt;\"4\",\"gns:ADM1\"=&gt;...</td>\n",
       "      <td>POINT (104.06337 30.65986)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>244083651</td>\n",
       "      <td>成华区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.13584 30.67823)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>244083653</td>\n",
       "      <td>青羊区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.00579 30.67602)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>244083654</td>\n",
       "      <td>锦江区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.11438 30.60134)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>244083655</td>\n",
       "      <td>武侯区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.04051 30.64389)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5959</th>\n",
       "      <td>9809427441</td>\n",
       "      <td>全记传统粤菜</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"amenity\"=&gt;\"restaurant\",\"cuisine\"=&gt;\"粤菜\"</td>\n",
       "      <td>POINT (104.04631 30.61888)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5960</th>\n",
       "      <td>9809427442</td>\n",
       "      <td>紫荆西路</td>\n",
       "      <td>None</td>\n",
       "      <td>bus_stop</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"bus\"=&gt;\"yes\",\"public_transport\"=&gt;\"platform\"</td>\n",
       "      <td>POINT (104.04662 30.61879)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5961</th>\n",
       "      <td>9809427443</td>\n",
       "      <td>新希望路口</td>\n",
       "      <td>None</td>\n",
       "      <td>bus_stop</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"bus\"=&gt;\"yes\",\"public_transport\"=&gt;\"platform\"</td>\n",
       "      <td>POINT (104.07049 30.62244)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5962</th>\n",
       "      <td>9809427446</td>\n",
       "      <td>None</td>\n",
       "      <td>lift_gate</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (104.11861 30.62089)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5963</th>\n",
       "      <td>9809427456</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"entrance\"=&gt;\"yes\"</td>\n",
       "      <td>POINT (104.11883 30.62204)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5964 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          osm_id    name    barrier   highway   ref address is_in place  \\\n",
       "0      244077729     成都市       None      None  None    None  None  city   \n",
       "1      244083651     成华区       None      None  None    None  None  city   \n",
       "2      244083653     青羊区       None      None  None    None  None  city   \n",
       "3      244083654     锦江区       None      None  None    None  None  city   \n",
       "4      244083655     武侯区       None      None  None    None  None  city   \n",
       "...          ...     ...        ...       ...   ...     ...   ...   ...   \n",
       "5959  9809427441  全记传统粤菜       None      None  None    None  None  None   \n",
       "5960  9809427442    紫荆西路       None  bus_stop  None    None  None  None   \n",
       "5961  9809427443   新希望路口       None  bus_stop  None    None  None  None   \n",
       "5962  9809427446    None  lift_gate      None  None    None  None  None   \n",
       "5963  9809427456    None       None      None     1    None  None  None   \n",
       "\n",
       "     man_made                                         other_tags  \\\n",
       "0        None  \"admin_level\"=>\"4\",\"capital\"=>\"4\",\"gns:ADM1\"=>...   \n",
       "1        None  \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "2        None  \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "3        None  \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "4        None  \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "...       ...                                                ...   \n",
       "5959     None            \"amenity\"=>\"restaurant\",\"cuisine\"=>\"粤菜\"   \n",
       "5960     None        \"bus\"=>\"yes\",\"public_transport\"=>\"platform\"   \n",
       "5961     None        \"bus\"=>\"yes\",\"public_transport\"=>\"platform\"   \n",
       "5962     None                                               None   \n",
       "5963     None                                  \"entrance\"=>\"yes\"   \n",
       "\n",
       "                        geometry  \n",
       "0     POINT (104.06337 30.65986)  \n",
       "1     POINT (104.13584 30.67823)  \n",
       "2     POINT (104.00579 30.67602)  \n",
       "3     POINT (104.11438 30.60134)  \n",
       "4     POINT (104.04051 30.64389)  \n",
       "...                          ...  \n",
       "5959  POINT (104.04631 30.61888)  \n",
       "5960  POINT (104.04662 30.61879)  \n",
       "5961  POINT (104.07049 30.62244)  \n",
       "5962  POINT (104.11861 30.62089)  \n",
       "5963  POINT (104.11883 30.62204)  \n",
       "\n",
       "[5964 rows x 11 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 2. 指定编码为gbk\n",
    "ptlayer = gpd.read_file('./data/ptgbk.shp', encoding='gbk')\n",
    "ptlayer.plot()\n",
    "plt.show()\n",
    "ptlayer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>osm_id</th>\n",
       "      <th>name</th>\n",
       "      <th>barrier</th>\n",
       "      <th>highway</th>\n",
       "      <th>ref</th>\n",
       "      <th>address</th>\n",
       "      <th>is_in</th>\n",
       "      <th>place</th>\n",
       "      <th>man_made</th>\n",
       "      <th>other_tags</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>244077729</td>\n",
       "      <td>成都市</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"admin_level\"=&gt;\"4\",\"capital\"=&gt;\"4\",\"gns:ADM1\"=&gt;...</td>\n",
       "      <td>POINT (104.06337 30.65986)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>244083651</td>\n",
       "      <td>成华区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.13584 30.67823)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>244083653</td>\n",
       "      <td>青羊区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.00579 30.67602)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>244083654</td>\n",
       "      <td>锦江区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.11438 30.60134)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>244083655</td>\n",
       "      <td>武侯区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.04051 30.64389)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>244083656</td>\n",
       "      <td>金牛区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.04180 30.71030)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>288416323</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>traffic_signals</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"traffic_signals\"=&gt;\"signal\"</td>\n",
       "      <td>POINT (104.11213 30.75041)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      osm_id  name barrier          highway   ref address is_in place  \\\n",
       "0  244077729   成都市    None             None  None    None  None  city   \n",
       "1  244083651   成华区    None             None  None    None  None  city   \n",
       "2  244083653   青羊区    None             None  None    None  None  city   \n",
       "3  244083654   锦江区    None             None  None    None  None  city   \n",
       "4  244083655   武侯区    None             None  None    None  None  city   \n",
       "5  244083656   金牛区    None             None  None    None  None  city   \n",
       "6  288416323  None    None  traffic_signals  None    None  None  None   \n",
       "\n",
       "  man_made                                         other_tags  \\\n",
       "0     None  \"admin_level\"=>\"4\",\"capital\"=>\"4\",\"gns:ADM1\"=>...   \n",
       "1     None  \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "2     None  \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "3     None  \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "4     None  \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "5     None  \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "6     None                        \"traffic_signals\"=>\"signal\"   \n",
       "\n",
       "                     geometry  \n",
       "0  POINT (104.06337 30.65986)  \n",
       "1  POINT (104.13584 30.67823)  \n",
       "2  POINT (104.00579 30.67602)  \n",
       "3  POINT (104.11438 30.60134)  \n",
       "4  POINT (104.04051 30.64389)  \n",
       "5  POINT (104.04180 30.71030)  \n",
       "6  POINT (104.11213 30.75041)  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 3. 读取指定的行\n",
    "ptlayer7 = gpd.read_file('./data/ptgbk.shp',encoding='gbk', rows=7)\n",
    "ptlayer7.plot()\n",
    "plt.show()\n",
    "ptlayer7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>osm_id</th>\n",
       "      <th>name</th>\n",
       "      <th>barrier</th>\n",
       "      <th>highway</th>\n",
       "      <th>ref</th>\n",
       "      <th>address</th>\n",
       "      <th>is_in</th>\n",
       "      <th>place</th>\n",
       "      <th>man_made</th>\n",
       "      <th>other_tags</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>244083653</td>\n",
       "      <td>青羊区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.00579 30.67602)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>244083655</td>\n",
       "      <td>武侯区</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>city</td>\n",
       "      <td>None</td>\n",
       "      <td>\"capital\"=&gt;\"6\",\"gns:ADM1\"=&gt;\"32\",\"gns:DSG\"=&gt;\"AD...</td>\n",
       "      <td>POINT (104.04051 30.64389)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>314623141</td>\n",
       "      <td>锦里</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"name:en\"=&gt;\"Jinli Ancient Street\",\"name:zh\"=&gt;\"...</td>\n",
       "      <td>POINT (104.04738 30.64848)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>314655392</td>\n",
       "      <td>中国建设银行</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"amenity\"=&gt;\"bank\",\"brand\"=&gt;\"中国建设银行\",\"brand:en\"...</td>\n",
       "      <td>POINT (104.04737 30.64656)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>314655401</td>\n",
       "      <td>中国建设银行</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"amenity\"=&gt;\"bank\",\"brand\"=&gt;\"中国建设银行\",\"brand:en\"...</td>\n",
       "      <td>POINT (104.03868 30.64674)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395</th>\n",
       "      <td>9566442886</td>\n",
       "      <td>None</td>\n",
       "      <td>lift_gate</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (104.01624 30.66455)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>396</th>\n",
       "      <td>9566442896</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"entrance\"=&gt;\"yes\"</td>\n",
       "      <td>POINT (104.01647 30.66320)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>397</th>\n",
       "      <td>9566442897</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>tower</td>\n",
       "      <td>None</td>\n",
       "      <td>POINT (104.01598 30.66342)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>398</th>\n",
       "      <td>9717613598</td>\n",
       "      <td>抚琴</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"name:en\"=&gt;\"Fuqin\",\"public_transport\"=&gt;\"stop_p...</td>\n",
       "      <td>POINT (104.03929 30.67905)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>399</th>\n",
       "      <td>9717613606</td>\n",
       "      <td>花牌坊</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>\"name:en\"=&gt;\"Huapaifang\",\"public_transport\"=&gt;\"s...</td>\n",
       "      <td>POINT (104.04629 30.68596)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>400 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         osm_id    name    barrier highway   ref address is_in place man_made  \\\n",
       "0     244083653     青羊区       None    None  None    None  None  city     None   \n",
       "1     244083655     武侯区       None    None  None    None  None  city     None   \n",
       "2     314623141      锦里       None    None  None    None  None  None     None   \n",
       "3     314655392  中国建设银行       None    None  None    None  None  None     None   \n",
       "4     314655401  中国建设银行       None    None  None    None  None  None     None   \n",
       "..          ...     ...        ...     ...   ...     ...   ...   ...      ...   \n",
       "395  9566442886    None  lift_gate    None  None    None  None  None     None   \n",
       "396  9566442896    None       None    None     1    None  None  None     None   \n",
       "397  9566442897    None       None    None  None    None  None  None    tower   \n",
       "398  9717613598      抚琴       None    None  None    None  None  None     None   \n",
       "399  9717613606     花牌坊       None    None  None    None  None  None     None   \n",
       "\n",
       "                                            other_tags  \\\n",
       "0    \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "1    \"capital\"=>\"6\",\"gns:ADM1\"=>\"32\",\"gns:DSG\"=>\"AD...   \n",
       "2    \"name:en\"=>\"Jinli Ancient Street\",\"name:zh\"=>\"...   \n",
       "3    \"amenity\"=>\"bank\",\"brand\"=>\"中国建设银行\",\"brand:en\"...   \n",
       "4    \"amenity\"=>\"bank\",\"brand\"=>\"中国建设银行\",\"brand:en\"...   \n",
       "..                                                 ...   \n",
       "395                                               None   \n",
       "396                                  \"entrance\"=>\"yes\"   \n",
       "397                                               None   \n",
       "398  \"name:en\"=>\"Fuqin\",\"public_transport\"=>\"stop_p...   \n",
       "399  \"name:en\"=>\"Huapaifang\",\"public_transport\"=>\"s...   \n",
       "\n",
       "                       geometry  \n",
       "0    POINT (104.00579 30.67602)  \n",
       "1    POINT (104.04051 30.64389)  \n",
       "2    POINT (104.04738 30.64848)  \n",
       "3    POINT (104.04737 30.64656)  \n",
       "4    POINT (104.03868 30.64674)  \n",
       "..                          ...  \n",
       "395  POINT (104.01624 30.66455)  \n",
       "396  POINT (104.01647 30.66320)  \n",
       "397  POINT (104.01598 30.66342)  \n",
       "398  POINT (104.03929 30.67905)  \n",
       "399  POINT (104.04629 30.68596)  \n",
       "\n",
       "[400 rows x 11 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 4 指定范围内\n",
    "ptlayer2 = gpd.read_file('./data/ptgbk.shp', encoding='gbk', bbox=(104, 30.64, 104.05, 30.7)) #(minx, miny, maxx, maxy)\n",
    "ptlayer2.plot()\n",
    "plt.show()\n",
    "ptlayer2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 加载`postgis`数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 创建连接的engine\n",
    "engine = create_engine('postgresql://postgres:admin@localhost:5432/gis')\n",
    "sql = 'SELECT * FROM parks'\n",
    "gy = gpd.read_postgis(sql, con=engine, geom_col='geom')\n",
    "gy.plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "gdf = gpd.read_file('./data/parks/parks.shp')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 加载CSV自定义点图层"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "加载步骤：\n",
    "1. 使用`pandas`的`read_csv()`读取文件\n",
    "2. 根据经纬度字段构建`GeoSeries`\n",
    "3. 组合`GeoSeries`和剩下的属性数据生成`GeoDataFrame`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>addr</th>\n",
       "      <th>tel</th>\n",
       "      <th>lon</th>\n",
       "      <th>lat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>人民公园</td>\n",
       "      <td>成都市区青羊区祠堂街9号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.063684</td>\n",
       "      <td>30.663607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>青龙湖湿地公园</td>\n",
       "      <td>成都市龙泉驿区成洛大道</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.199156</td>\n",
       "      <td>30.645796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>天府公园</td>\n",
       "      <td>杭州路东段与蜀州路交叉口西南150米</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.085714</td>\n",
       "      <td>30.443121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>香草湖湿地公园</td>\n",
       "      <td>四川省成都市郫都区蜀源大道二段</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.965884</td>\n",
       "      <td>30.844136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>麓湖生态城红石公园</td>\n",
       "      <td>成都市天府新区华阳街道天府大道南一段</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.085120</td>\n",
       "      <td>30.466655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name                addr  tel         lon        lat\n",
       "0       人民公园        成都市区青羊区祠堂街9号  NaN  104.063684  30.663607\n",
       "1    青龙湖湿地公园         成都市龙泉驿区成洛大道  NaN  104.199156  30.645796\n",
       "2       天府公园  杭州路东段与蜀州路交叉口西南150米  NaN  104.085714  30.443121\n",
       "3    香草湖湿地公园     四川省成都市郫都区蜀源大道二段  NaN  103.965884  30.844136\n",
       "4  麓湖生态城红石公园  成都市天府新区华阳街道天府大道南一段  NaN  104.085120  30.466655"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1. 读取csv文件\n",
    "data = pd.read_csv('./data/parks.csv', encoding='gbk')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### `apply`函数\n",
    "> apply() 方法的第一个参数是一个回调函数，是必选参数，apply() 方法的 axis 参数可以指定遍历的轴，对行进行遍历时，需要将axis设置为1\n",
    "> 当axis=1时，apply() 方法的第一个参数，即回调函数中，会传入当前的行数据作为参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      POINT (104.063684 30.663607)\n",
       "1      POINT (104.199156 30.645796)\n",
       "2      POINT (104.085714 30.443121)\n",
       "3      POINT (103.965884 30.844136)\n",
       "4       POINT (104.08512 30.466655)\n",
       "                   ...             \n",
       "145    POINT (104.067981 30.568993)\n",
       "146    POINT (104.079769 30.568199)\n",
       "147    POINT (103.451982 30.406407)\n",
       "148    POINT (103.938903 30.731913)\n",
       "149    POINT (104.158602 30.787245)\n",
       "Length: 150, dtype: object"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 2. 构建GeoSeries\n",
    "confun = lambda x: Point(x['lon'], x['lat'])\n",
    "geoms = data.apply(confun, axis=1)\n",
    "geoms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>addr</th>\n",
       "      <th>tel</th>\n",
       "      <th>lon</th>\n",
       "      <th>lat</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>人民公园</td>\n",
       "      <td>成都市区青羊区祠堂街9号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.063684</td>\n",
       "      <td>30.663607</td>\n",
       "      <td>POINT (104.06368 30.66361)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>青龙湖湿地公园</td>\n",
       "      <td>成都市龙泉驿区成洛大道</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.199156</td>\n",
       "      <td>30.645796</td>\n",
       "      <td>POINT (104.19916 30.64580)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>天府公园</td>\n",
       "      <td>杭州路东段与蜀州路交叉口西南150米</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.085714</td>\n",
       "      <td>30.443121</td>\n",
       "      <td>POINT (104.08571 30.44312)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>香草湖湿地公园</td>\n",
       "      <td>四川省成都市郫都区蜀源大道二段</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.965884</td>\n",
       "      <td>30.844136</td>\n",
       "      <td>POINT (103.96588 30.84414)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>麓湖生态城红石公园</td>\n",
       "      <td>成都市天府新区华阳街道天府大道南一段</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.085120</td>\n",
       "      <td>30.466655</td>\n",
       "      <td>POINT (104.08512 30.46665)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>桂溪生态公园西区</td>\n",
       "      <td>四川省成都市武侯区天府一街北50米</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.067981</td>\n",
       "      <td>30.568993</td>\n",
       "      <td>POINT (104.06798 30.56899)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>桂溪生态公园东区</td>\n",
       "      <td>世纪城东路9号四川电视台对面</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.079769</td>\n",
       "      <td>30.568199</td>\n",
       "      <td>POINT (104.07977 30.56820)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>邛窑遗址公园</td>\n",
       "      <td>成都市邛崃市南河路</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.451982</td>\n",
       "      <td>30.406407</td>\n",
       "      <td>POINT (103.45198 30.40641)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>芙蓉长卷药博园</td>\n",
       "      <td>芙蓉大道与永宁大道交汇处东侧400米</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.938903</td>\n",
       "      <td>30.731913</td>\n",
       "      <td>POINT (103.93890 30.73191)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>人民的公园</td>\n",
       "      <td>蜀龙大道540号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.158602</td>\n",
       "      <td>30.787245</td>\n",
       "      <td>POINT (104.15860 30.78724)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          name                addr  tel         lon        lat  \\\n",
       "0         人民公园        成都市区青羊区祠堂街9号  NaN  104.063684  30.663607   \n",
       "1      青龙湖湿地公园         成都市龙泉驿区成洛大道  NaN  104.199156  30.645796   \n",
       "2         天府公园  杭州路东段与蜀州路交叉口西南150米  NaN  104.085714  30.443121   \n",
       "3      香草湖湿地公园     四川省成都市郫都区蜀源大道二段  NaN  103.965884  30.844136   \n",
       "4    麓湖生态城红石公园  成都市天府新区华阳街道天府大道南一段  NaN  104.085120  30.466655   \n",
       "..         ...                 ...  ...         ...        ...   \n",
       "145   桂溪生态公园西区   四川省成都市武侯区天府一街北50米  NaN  104.067981  30.568993   \n",
       "146   桂溪生态公园东区      世纪城东路9号四川电视台对面  NaN  104.079769  30.568199   \n",
       "147     邛窑遗址公园           成都市邛崃市南河路  NaN  103.451982  30.406407   \n",
       "148    芙蓉长卷药博园  芙蓉大道与永宁大道交汇处东侧400米  NaN  103.938903  30.731913   \n",
       "149      人民的公园            蜀龙大道540号  NaN  104.158602  30.787245   \n",
       "\n",
       "                       geometry  \n",
       "0    POINT (104.06368 30.66361)  \n",
       "1    POINT (104.19916 30.64580)  \n",
       "2    POINT (104.08571 30.44312)  \n",
       "3    POINT (103.96588 30.84414)  \n",
       "4    POINT (104.08512 30.46665)  \n",
       "..                          ...  \n",
       "145  POINT (104.06798 30.56899)  \n",
       "146  POINT (104.07977 30.56820)  \n",
       "147  POINT (103.45198 30.40641)  \n",
       "148  POINT (103.93890 30.73191)  \n",
       "149  POINT (104.15860 30.78724)  \n",
       "\n",
       "[150 rows x 6 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 3 组合属性数据和geoseries\n",
    "parkslayer1 = gpd.GeoDataFrame(data, geometry=geoms)\n",
    "parkslayer1.plot()\n",
    "plt.show()\n",
    "parkslayer1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 根据属性信息选择数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. 编写一个函数，其输入为一条记录（一行数据），在函数里完成该条记录是否满足条件的判断，满足返回 `True`，不满足返回 `False`\n",
    "\n",
    "2. 使用被选择图层`（GeoDataFrame）`对象的` apply()`方法，传入上一步的函数，并设置参数`axis=1`，将编写的函数对图层中的所有行进行测试，得到一个由布尔值构成的`Series`对象，作为布尔选择索引蒙板(`mask`)\n",
    "\n",
    "3. 利用得到的选择索引蒙板(`mask`)，取得满足条件的数据，完成选择。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "成都市区青羊区祠堂街9号 True\n",
      "成都市龙泉驿区成洛大道 False\n"
     ]
    }
   ],
   "source": [
    "def filterfunc(row):\n",
    "    addr = row['addr']\n",
    "    return '青羊区' in addr\n",
    "print(parkslayer.loc[0, 'addr'], filterfunc(parkslayer.loc[0]))\n",
    "print(parkslayer.loc[1, 'addr'], filterfunc(parkslayer.loc[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       True\n",
       "1      False\n",
       "2      False\n",
       "3      False\n",
       "4      False\n",
       "       ...  \n",
       "145    False\n",
       "146    False\n",
       "147    False\n",
       "148    False\n",
       "149    False\n",
       "Length: 150, dtype: bool"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask = parkslayer.apply(filterfunc, axis=1)\n",
    "mask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>addr</th>\n",
       "      <th>tel</th>\n",
       "      <th>lon</th>\n",
       "      <th>lat</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>人民公园</td>\n",
       "      <td>成都市区青羊区祠堂街9号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.063684</td>\n",
       "      <td>30.663607</td>\n",
       "      <td>POINT (104.06368 30.66361)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>成飞公园</td>\n",
       "      <td>成都市青羊区纬一路220号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.963681</td>\n",
       "      <td>30.705630</td>\n",
       "      <td>POINT (103.96368 30.70563)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>石人公园</td>\n",
       "      <td>成都市青羊区石人北路2号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.036200</td>\n",
       "      <td>30.681889</td>\n",
       "      <td>POINT (104.03620 30.68189)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>百花潭公园</td>\n",
       "      <td>成都市青羊区芳邻路5号</td>\n",
       "      <td>(028)87014534</td>\n",
       "      <td>104.050045</td>\n",
       "      <td>30.662355</td>\n",
       "      <td>POINT (104.05004 30.66236)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>文化公园</td>\n",
       "      <td>成都市青羊区琴台路73号</td>\n",
       "      <td>(028)87769637</td>\n",
       "      <td>104.049488</td>\n",
       "      <td>30.666781</td>\n",
       "      <td>POINT (104.04949 30.66678)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>苏坡公园</td>\n",
       "      <td>四川省成都市青羊区西环三路四段341附近</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.004957</td>\n",
       "      <td>30.696323</td>\n",
       "      <td>POINT (104.00496 30.69632)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>东坡体育公园</td>\n",
       "      <td>成都市青羊区东坡南一路</td>\n",
       "      <td>(028)81720085</td>\n",
       "      <td>104.001763</td>\n",
       "      <td>30.661989</td>\n",
       "      <td>POINT (104.00176 30.66199)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>大公园</td>\n",
       "      <td>四川省成都市青羊区光华大道跟成飞大道交叉口</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.966275</td>\n",
       "      <td>30.676301</td>\n",
       "      <td>POINT (103.96627 30.67630)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      name                   addr            tel         lon        lat  \\\n",
       "0     人民公园           成都市区青羊区祠堂街9号            NaN  104.063684  30.663607   \n",
       "11    成飞公园          成都市青羊区纬一路220号            NaN  103.963681  30.705630   \n",
       "25    石人公园           成都市青羊区石人北路2号            NaN  104.036200  30.681889   \n",
       "26   百花潭公园            成都市青羊区芳邻路5号  (028)87014534  104.050045  30.662355   \n",
       "27    文化公园           成都市青羊区琴台路73号  (028)87769637  104.049488  30.666781   \n",
       "70    苏坡公园   四川省成都市青羊区西环三路四段341附近            NaN  104.004957  30.696323   \n",
       "75  东坡体育公园            成都市青羊区东坡南一路  (028)81720085  104.001763  30.661989   \n",
       "95     大公园  四川省成都市青羊区光华大道跟成飞大道交叉口            NaN  103.966275  30.676301   \n",
       "\n",
       "                      geometry  \n",
       "0   POINT (104.06368 30.66361)  \n",
       "11  POINT (103.96368 30.70563)  \n",
       "25  POINT (104.03620 30.68189)  \n",
       "26  POINT (104.05004 30.66236)  \n",
       "27  POINT (104.04949 30.66678)  \n",
       "70  POINT (104.00496 30.69632)  \n",
       "75  POINT (104.00176 30.66199)  \n",
       "95  POINT (103.96627 30.67630)  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qyparks = parkslayer[mask]\n",
    "qyparks.plot()\n",
    "plt.show()\n",
    "qyparks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 根据几何信息选择数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> 相关的方法\n",
    "\n",
    "| 方法名 | 说明 |\n",
    "|--|--|\n",
    "| contains | 是否包含另一个几何对象 |\n",
    "| crosses | 是否与另一个几何对象相交 |\n",
    "| disjoint | 是否与另一个几何对象相离 |\n",
    "| geom_equals | 是否与另一个几何对象完全一致 |\n",
    "| intersects | 是否与另一个几何对象相交 |\n",
    "| touches | 是否与另一个几何对象相邻 |\n",
    "| within | 是否在另一个几何对象内部 |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 两个图层叠加显示\n",
    "ax = polylayer.plot(color=(1,0,0,0.7))\n",
    "parkslayer.plot(ax=ax, marker='.')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       True\n",
       "1       True\n",
       "2      False\n",
       "3      False\n",
       "4      False\n",
       "       ...  \n",
       "145    False\n",
       "146     True\n",
       "147    False\n",
       "148     True\n",
       "149    False\n",
       "Length: 150, dtype: bool"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cdgeom=polylayer.loc[0, 'geometry']\n",
    "mask3=parkslayer.within(cdgeom)\n",
    "mask3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>addr</th>\n",
       "      <th>tel</th>\n",
       "      <th>lon</th>\n",
       "      <th>lat</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>人民公园</td>\n",
       "      <td>成都市区青羊区祠堂街9号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.063684</td>\n",
       "      <td>30.663607</td>\n",
       "      <td>POINT (104.06368 30.66361)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>青龙湖湿地公园</td>\n",
       "      <td>成都市龙泉驿区成洛大道</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.199156</td>\n",
       "      <td>30.645796</td>\n",
       "      <td>POINT (104.19916 30.64580)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>东湖公园</td>\n",
       "      <td>成都市锦江区二环路东五段299号</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.094487</td>\n",
       "      <td>30.621803</td>\n",
       "      <td>POINT (104.09449 30.62180)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>新华公园</td>\n",
       "      <td>四川省成都市成华区双林路87号</td>\n",
       "      <td>(028)84382816</td>\n",
       "      <td>104.112282</td>\n",
       "      <td>30.662277</td>\n",
       "      <td>POINT (104.11228 30.66228)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>清水河公园</td>\n",
       "      <td>成都市武侯区西三环路三段</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.993573</td>\n",
       "      <td>30.664697</td>\n",
       "      <td>POINT (103.99357 30.66470)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>熊猫体育公园</td>\n",
       "      <td>龙青路</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.177908</td>\n",
       "      <td>30.727070</td>\n",
       "      <td>POINT (104.17791 30.72707)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>中海体育公园</td>\n",
       "      <td>蜀西路339号北侧</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.977055</td>\n",
       "      <td>30.726649</td>\n",
       "      <td>POINT (103.97705 30.72665)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>成都星秀领域体育公园</td>\n",
       "      <td>四川省成都市武侯区万顺一路</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.992879</td>\n",
       "      <td>30.658824</td>\n",
       "      <td>POINT (103.99288 30.65882)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>桂溪生态公园东区</td>\n",
       "      <td>世纪城东路9号四川电视台对面</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104.079769</td>\n",
       "      <td>30.568199</td>\n",
       "      <td>POINT (104.07977 30.56820)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>芙蓉长卷药博园</td>\n",
       "      <td>芙蓉大道与永宁大道交汇处东侧400米</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103.938903</td>\n",
       "      <td>30.731913</td>\n",
       "      <td>POINT (103.93890 30.73191)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>63 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           name                addr            tel         lon        lat  \\\n",
       "0          人民公园        成都市区青羊区祠堂街9号            NaN  104.063684  30.663607   \n",
       "1       青龙湖湿地公园         成都市龙泉驿区成洛大道            NaN  104.199156  30.645796   \n",
       "5          东湖公园    成都市锦江区二环路东五段299号            NaN  104.094487  30.621803   \n",
       "6          新华公园     四川省成都市成华区双林路87号  (028)84382816  104.112282  30.662277   \n",
       "8         清水河公园        成都市武侯区西三环路三段            NaN  103.993573  30.664697   \n",
       "..          ...                 ...            ...         ...        ...   \n",
       "115      熊猫体育公园                 龙青路            NaN  104.177908  30.727070   \n",
       "130      中海体育公园           蜀西路339号北侧            NaN  103.977055  30.726649   \n",
       "143  成都星秀领域体育公园       四川省成都市武侯区万顺一路            NaN  103.992879  30.658824   \n",
       "146    桂溪生态公园东区      世纪城东路9号四川电视台对面            NaN  104.079769  30.568199   \n",
       "148     芙蓉长卷药博园  芙蓉大道与永宁大道交汇处东侧400米            NaN  103.938903  30.731913   \n",
       "\n",
       "                       geometry  \n",
       "0    POINT (104.06368 30.66361)  \n",
       "1    POINT (104.19916 30.64580)  \n",
       "5    POINT (104.09449 30.62180)  \n",
       "6    POINT (104.11228 30.66228)  \n",
       "8    POINT (103.99357 30.66470)  \n",
       "..                          ...  \n",
       "115  POINT (104.17791 30.72707)  \n",
       "130  POINT (103.97705 30.72665)  \n",
       "143  POINT (103.99288 30.65882)  \n",
       "146  POINT (104.07977 30.56820)  \n",
       "148  POINT (103.93890 30.73191)  \n",
       "\n",
       "[63 rows x 6 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ftptlayer=parkslayer[mask3]\n",
    "ftptlayer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = polylayer.plot(color=(1,0,0,0.3))\n",
    "ftptlayer.plot(ax=ax, marker='.')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmQAAAG7CAYAAABtkYnbAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdeXyU1b348c8zazKTfSELhBD2JUEiWkhSrApCKYtWBaG3CIr2Xu+tisLvd2trBfsDwWprte3Vey0tKFpaFbxQqywqKJtCIOyGQBKSkH2bSSaZ7Znn98fAQCQhM8kkk+W8X695aZ45z3m+k4TMd85zzvdIiqIoCIIgCIIgCAGjCnQAgiAIgiAI/Z1IyARBEARBEAJMJGSCIAiCIAgBJhIyQRAEQRCEABMJmSAIgiAIQoCJhEwQBEEQBCHAREImCIIgCIIQYCIhEwRBEARBCDBNoAMQBEEQBME/XC4Xdrs90GEIl2m1WtRqtVdtRUImCIIgCH2A3W6noKAAl8sV6FCEa0RERBAfH48kSTdsJxIyQRAEQejlFEWhrKwMtVpNUlISKpWYkRRoiqLQ1NREZWUlAAkJCTdsLxIyQRAEQejlnE4nTU1NJCYmYjAYAh2OcFlwcDAAlZWVDBgw4Ia3L0UKLQiCIAi9nCzLAOh0ugBHInzblQTZ4XDcsJ1IyARBEAShj2hvnpLQ/bz9mYhbloIgCIIgAGC5VEXprmwc5ia0YQYS75qIcWBsoMPqF0RCJgiCIAj9XPWRXI6vfZfi7QdRnLLnuKRRkzQng5ue+RExt4wKYIR9n7hlKQiCIAj92MWt+/jnlCcp2rqvRTIGoDhlii4/f/HDfX6/9qpVq5AkqcUjPj7e8/yWLVuYMWMGMTExSJJETk7OdX3YbDYef/xxYmJiMBqNzJ07l5KSkhZt1qxZQ2ZmJgaDgYiIiFZjKSoqYs6cORiNRmJiYnjiiSfarOl2/vx5QkND2+yrI0RCJgiCIAj9VPWRXPb+aDWy7cYTzmWbg70LV1N9JNfvMYwbN46ysjLP4+TJk57nLBYLWVlZrFu3rs3zly1bxtatW9m8eTP79u2jsbGR2bNnexY6gLtG27x583jsscda7UOWZWbNmoXFYmHfvn1s3ryZDz74gOXLl1/X1uFwsHDhQqZMmdKJV309cctSEARBEPqp42vfbTcZu0K2OTix7q/c+f4qv8ag0WhajIpda9GiRQAUFha2+rzJZGL9+vW8/fbbTJs2DYBNmzaRlJTE7t27mTFjBgDPP/88ABs2bGi1n507d3LmzBmKi4tJTEwE4De/+Q1LlixhzZo1hIWFedo+++yzjB49mqlTp3LgwAGfX29bxAiZIAiCIPRDlktVFG/zLaEo2nYAy6Uqv8aRl5dHYmIiKSkpLFiwgPz8fK/Pzc7OxuFwMH36dM+xxMREUlNTfUqWDh48SGpqqicZA5gxYwY2m43s7GzPsc8++4z33nuPP/7xj1737S2RkAmCIAhCP1S6KxtF9m2bJcUpU7r7qN9imDRpEm+99RY7duzgzTffpLy8nMzMTGpqarw6v7y8HJ1OR2RkZIvjcXFxlJeXex1HeXk5cXFxLY5FRkai0+k8/dTU1LBkyRI2bNjQYsTMX8QtS0EQBEHohxzmpm49rzUzZ870/H9aWhoZGRkMGzaMjRs38vTTT3e4X0VRfK7J1lr7a/t59NFH+dGPfsRtt93W4bhuRIyQCYIgCEI/pA3r2BZLHT3PG0ajkbS0NPLy8rxqHx8fj91up66ursXxysrK60a82uvn2yNqdXV1OBwOTz+fffYZL7/8MhqNBo1Gw9KlSzGZTGg0Gv785z97fa22iIRMEARBEPqhxLsmImna3luxNZJGTeK0m7soIncJi7Nnz7a7EfcVEydORKvVsmvXLs+xsrIyTp06RWZmptfXzcjI4NSpU5SVlXmO7dy5E71ez8SJEwH3PLOcnBzP41e/+hWhoaHk5OTwwx/+0OtrtUXcshQEQRCEfsg4MJakORkUbfW+vtjguZl+rdy/YsUK5syZw+DBg6msrGT16tWYzWYWL14MQG1tLUVFRZSWlgKQm+suuxEfH098fDzh4eEsXbqU5cuXEx0dTVRUFCtWrCAtLc2z6hLcNcau9CXLsqee2fDhwwkJCWH69OmMHTuWRYsW8dJLL1FbW8uKFSt49NFHPfPFxowZ0yL2I0eOoFKpSE1N9cv3QoyQCYIgCEI/ddMzP0Kt13rVVh2kY/zPFvr1+iUlJSxcuJBRo0Zx7733otPpOHToEMnJyQBs27aN9PR0Zs2aBcCCBQtIT0/njTfe8PTxyiuvcM899zB//nyysrIwGAxs374dtfrq6N9zzz1Heno6K1eupLGxkfT0dNLT0zly5Ij7tanVfPTRRwQFBZGVlcX8+fO55557ePnll/36em9EUhRF6barCYIgCILgd1arlYKCAlJSUggKCvLp3Isf7mPvwhsXh1XrtXzvr8+SfM93Oxtqv+Ptz0aMkAmCIAhCP5Z8z3f5wZevknzvlOvmlEkaNcn3TnE/L5KxLiXmkAmCIAhCPxdzyyjufH8VlktVlO4+isPchDbMQOK0m/06Z0xom0jIBEEQBEEA3BP9RyyeEegw+iVxy1IQBEEQBCHAREImCIIgCIIQYCIhEwRBEARBCDCRkAmCIAiCIASYSMgEQRAEQRACrM+ssnS5XJSWlhIaGurzDu+CIAiC0NMpikJDQwOJiYmoVF0znmItr6Z23zGcDU1oQg1EfTedoPiYLrmW8C1KH1FcXKwA4iEe4iEe4iEeffpRXFx83Xtgc3OzcubMGaW5ublD76H1x3OVnH/9f8qu4bOVnUNmeh67hs9Wcv71/yn1x3M7+zbdqpUrV173+uLi4jzPf/DBB8r06dOV6OhoBVCOHTt2XR9Wq1X56U9/qkRHRysGg0GZM2fOdd+j1atXKxkZGUpwcLASHh7eaiwXL15UZs+erRgMBiU6Olp5/PHHFZvN5nm+oKCg1Z/Hxx9/fMPX6O3Pps+MkIWGhgJQXFzs2QhUEARBEPoKs9lMUlKS5/3OXyp3HODkEy/isl+/dZLilKnccYDqzw+T9vv/ZMD0TL9eG2DcuHHs3r3b8/W1e1BaLBaysrKYN28ejz76aKvnL1u2jO3bt7N582aio6NZvnw5s2fPJjs729OX3W5n3rx5ZGRksH79+uv6kGWZWbNmERsby759+6ipqWHx4sUoisLvf//7Fm13797NuHHjPF9HRUV16vVf0WcSsiu3KcPCwkRCJgiCIPRZ/pyWYzpxrs1k7Fouu4OTj7/ILe+9RPj4kX67PoBGoyE+Pr7V5xYtWgRAYWFhq8+bTCbWr1/P22+/zbRp0wDYtGkTSUlJ7N69mxkz3EVun3/+eQA2bNjQaj87d+7kzJkzFBcXk5iYCMBvfvMblixZwpo1a1rkFdHR0W3G2xliUr8gCIIg9FOF//X3dpOxK1x2B4Wv/93vMeTl5ZGYmEhKSgoLFiwgPz/f63Ozs7NxOBxMnz7dcywxMZHU1FQOHDjgdT8HDx4kNTXVk4wBzJgxA5vNRnZ2dou2c+fOZcCAAWRlZfH+++97fY32iIRMEARBEPoha3k1VbsP+XRO1e6vsJZX+y2GSZMm8dZbb7Fjxw7efPNNysvLyczMpKamxqvzy8vL0el0REZGtjgeFxdHeXm513GUl5cTFxfX4lhkZCQ6nc7TT0hICL/97W95//33+ec//8nUqVN54IEH2LRpk9fXuZE+c8tSEARBEATv1e47hiK7fDpHccrU7s8h8b5pfolh5syZnv9PS0sjIyODYcOGsXHjRp5++ukO96sois+3dltrf20/MTExPPXUU57nbrnlFurq6vj1r3/Nj3/84w7HeoUYIRMEQRCEfsjZ0NSt53nDaDSSlpZGXl6eV+3j4+Ox2+3U1dW1OF5ZWXndiFd7/Xx7RK2urg6Hw3HDfiZPnux1rO0RCZkgCIIg9EOaUEO3nucNm83G2bNnSUhI8Kr9xIkT0Wq17Nq1y3OsrKyMU6dOkZnp/YrQjIwMTp06RVlZmefYzp070ev1TJw4sc3zjh075nWs7RG3LAVBEAShH4r6bjqSRo3ilL0+R9Koicqa4LcYVqxYwZw5cxg8eDCVlZWsXr0as9nM4sWLAaitraWoqIjS0lIAcnNzAfeIVnx8POHh4SxdupTly5cTHR1NVFQUK1asIC0tzbPqEqCoqMjTlyzL5OTkADB8+HBCQkKYPn06Y8eOZdGiRbz00kvU1tayYsUKHn30Uc8Ky40bN6LVaklPT0elUrF9+3Zee+01XnzxRb98L0RCJgiCIAj9UFB8DLFTJ1G5w/vViLHTJvm1cn9JSQkLFy6kurqa2NhYJk+ezKFDh0hOTgZg27ZtPPTQQ572CxYsAGDlypWsWrUKgFdeeQWNRsP8+fNpbm5m6tSpbNiwoUU9s+eee46NGzd6vk5PTwfg888/5/bbb0etVvPRRx/x7//+72RlZREcHMyPfvQjXn755Rbxrl69mosXL6JWqxk5ciR//vOf/TJ/DEBSFEXxS08BZjabCQ8Px2QyiTpkgiAIQp9zo/c5q9VKQUEBKSkpBAUFed2n6cQ5jsz7P16VvlDpddzy91/7vQ5ZX+ftz0bMIRMEQRCEfip8/EjSfv+fqHTaG7ZT6bSkvfZ/RTLWhURCJgiCIAj92IDpmdzy3ksM+H4mkkbd4jlJo2bA9y8/3wXbJglXiTlkgiAIgtDPhY8fyU2vP4u1vJra/Tk4G5rQhBqIyprg1zljQttEQiYIgiAIAuCe6O+voq+Cb8QtS0EQBEEQhAATCZkg9HA2p5Pcmlps19QK+vpSGX8//Q2Vlq6rmC0IgiB0H3HLUhB6qNrmZt47c44vioppcjgBCNfriTUGU1hvwulS+KKohD/MFLcXBEEQejuRkAlCD3TRZGblnv2YbLYWx002W4tjFRYLLkVB5eMmuoIgCELPIhIyQehBvrpUxteXyjhSVo7ZZm+3vdOlcNFkJiUivN22lxoaiTcaUKuuzlQw2+wEadTo1OobnCkIgiB0NZGQCUIPILsUzlRX89KBr5F93DzjhX2HWHPHdxlgNLbZ5rOCi/zxyDGmpQzh3ybehCRJNNjsPPPZF8guF7+e9j3C9PrOvgxBEHo5R1UNliM5uJqaURmCMd4yAW1sdKDD6hd8mtT/+uuvM378eMLCwggLCyMjI4OPP/7Y8/yWLVuYMWMGMTExSJLk2bzTW5s3b0aSJO655x6fzhOE3mznhULmf/C/PLdnv8/JGEB1UzO/3LOf6qYmmhwO/jf3PKcqq7lkbiC7rJx1+7/i94eP4VJgZ34hz+3dz28OHuann+ymtKGRCkuTV6NxgiD0Xc3fnKfkl+s4v+AnlL34eyp+/yfKXvw95xf8hJJfrqP5m/Ndct1Vq1YhSVKLR3x8vOd5b/IKm83G448/TkxMDEajkblz51JSUtKizZo1a8jMzMRgMBAREdFqLEVFRcyZMwej0UhMTAxPPPEEdnvLv42KovDyyy8zcuRI9Ho9SUlJvPDCC53+PoCPI2SDBg1i3bp1DB8+HHDvfH733Xdz7Ngxxo0bh8ViISsri3nz5vHoo4/6FMjFixdZsWIFU6ZM8ek8QejtKpuacHVyR9lKSxP/Z/deJCTqrNYbtj1VWd3i65HRkQwKC+1cAIIg9FrmLw9R+qvfoDha2c9Slmn48hCNh7IZ+NxyQqdM9vv1x40bx+7duz1fX7spuDd5xbJly9i+fTubN28mOjqa5cuXM3v2bLKzsz192e125s2bR0ZGBuvXr7+uD1mWmTVrFrGxsezbt4+amhoWL16Moij8/ve/97R78skn2blzJy+//DJpaWmYTCaqq6uv668jfErI5syZ0+LrNWvW8Prrr3Po0CHGjRvHokWLACgsLPQpCFmW+Zd/+Reef/55vvzyS+rr6306XxB6sxMVVX7pp95qa79RKwYYDH65viAIvU/zN+fbTsauoTgcXPrVb0j+/VqCRw/3awwajabFqNi12ssrTCYT69ev5+2332baNPeK802bNpGUlMTu3buZMWMGAM8//zwAGzZsaLWfnTt3cubMGYqLi0lMTATgN7/5DUuWLGHNmjWEhYVx9uxZXn/9dU6dOsWoUaM6+nLb1OE6ZLIss3nzZiwWCxkZGZ0K4le/+hWxsbEsXbq0U/0IQm9jsdvJr6sPaAzHK6pa1DgTBKH/qHnn/XaTsSsUh4Oad9/3ewx5eXkkJiaSkpLCggULyM/P9/rc7OxsHA4H06dP9xxLTEwkNTWVAwcOeN3PwYMHSU1N9SRjADNmzMBms5GdnQ3A9u3bGTp0KP/4xz9ISUlhyJAhPPLII9TW1np9nRvxeVL/yZMnycjIwGq1EhISwtatWxk7dmyHA9i/fz/r16/3eb6ZzWbDds3yf7PZ3OEYBKG7uRSFo2UV/PN8fofmjflTg93OB9+c40epYwIahyAI3ctRVUPD/q99Oqdh/2EcVTV+m+g/adIk3nrrLUaOHElFRQWrV68mMzOT06dPEx3d/jXKy8vR6XRERka2OB4XF0d5ebnXcZSXlxMXF9fiWGRkJDqdztNPfn4+Fy9e5L333uOtt95ClmWeeuop7r//fj777DOvr9UWnxOyUaNGkZOTQ319PR988AGLFy9m7969HUrKGhoa+PGPf8ybb75JTIxvm5euXbvWMwQpCL1Bo93Ox+cLaHY6KagzkVNRGeiQPN4/k8stCfGMjI5sv7EgCH2C5UgOuFy+nSTLWLKPE/H9O/0Sw8yZMz3/n5aWRkZGBsOGDWPjxo08/fTTHe5XURQkH+szttb+2n5cLhc2m82TQAKsX7+eiRMnkpub2+nbmD4nZDqdzjOp/5ZbbuHw4cO8+uqr/Pd//7fPF79w4QKFhYUt5qa5Lv9yaDQacnNzGTZsWKvnPvPMMy1+WGazmaSkJJ9jEISu4pBd/OzTvVQ2NRGs0VBnteLs7Oz9LqIAfzp2gnVTbxNFZgWhn3A1NXfwvK7bss1oNJKWlkZeXp5X7ePj47Hb7dTV1bUYJausrCQzM9Pr68bHx/PVV1+1OFZXV4fD4fCMnCUkJKDRaDzJGMCYMe47C0VFRZ1OyDq9l6WiKC1uHfpi9OjRnDx5kpycHM9j7ty53HHHHeTk5NwwwdLr9Z7yG1cegtCTnK2uIb/eRKPdQVVTc49Nxq7Iq63jUElpoMMQBKGbqAzBHTyv6xYC2Ww2zp49S0JCglftJ06ciFarZdeuXZ5jZWVlnDp1yqeELCMjg1OnTlFWVuY5tnPnTvR6PRMnTgQgKysLp9PJhQsXPG3OnTsHQHJystfXaotPI2Q///nPmTlzJklJSTQ0NLB582b27NnDJ598AkBtbS1FRUWUlrr/qOfm5gLuzPPKCooHH3yQgQMHsnbtWoKCgkhNTW1xjSv1Qb59XBB6k7pmK28eOxHoMHz2enYOqQNiRJFYQegHjLdMALUaZB8W9ajVGCfe5LcYVqxYwZw5cxg8eDCVlZWsXr0as9nM4sWLgfbzivDwcJYuXcry5cuJjo4mKiqKFStWkJaW5ll1Ce4RrCt9ybLsmbc+fPhwQkJCmD59OmPHjmXRokW89NJL1NbWsmLFCh599FHPgM+0adO4+eabefjhh/nd736Hy+XiP/7jP7jrrrtajJp1lE8jZBUVFSxatIhRo0YxdepUvvrqKz755BPuuusuALZt20Z6ejqzZs0CYMGCBaSnp/PGG2+0+KZcm4EKQl/T7HDwwv5DlJgbAh2KzxrtDt45eRYlwAsNBEHoetrYaEIzb/XpnNCsW/1aub+kpISFCxcyatQo7r33XnQ6HYcOHfKMOHmTV7zyyivcc889zJ8/n6ysLAwGA9u3b29Rz+y5554jPT2dlStX0tjYSHp6Ounp6Rw5cgRw1z776KOPCAoKIisri/nz53PPPffw8ssve/pQqVRs376dmJgYbrvtNmbNmsWYMWPYvHmzX74XktJH/vKazWbCw8MxmUzi9qUQMCcqqngjO4eyRkugQ+mUJTeN4+5RIwIdhiAI17jR+5zVaqWgoICUlBSCgoK87rP5m/NcfPwZr0pfSDodya+94Pc6ZH2dtz+bTs8hEwTB7VxNHav27u/1yRjAWydOU2wSpWQEoa8LHj2cgc8tR9Jqb9hO0moZ+MunRTLWhURCJgh+oCgK+0oK6RPDzYBLcddKEwSh7wudMpnk368l9LbJ7jll11KrCb3t8vNdsG2ScJXPZS8EQbjeZ6XfkN1wlvRBiRwrqQ90OH5xorKaxNBQtGrxuU0Q+rrg0cMZ9Kuf4aiqwZJ9HFdTEyqDAePEm/w6Z0xom0jIBKGTGh02Pi4+hSRBpVJKatxATlXUBTqsTvtzzkny6+p5ctLEQIciCEI30cZG+63oq+AbkZAJgpcaHTaanXaig4yoJPeoUUljHX/PP4xVvjoh1qGrQy1JAd8SyR8K602BDkEQBKFfEAmZIFz27vmvSDJGMSWh5erCC+ZKthQc42JjDQCh2iAy4oZyzlRBYUPNdf00upoYnxTL6UvN2GUftyXpYVIH+LalmSAIgtAxIiETBOBQZT4HKi4AF8hvqEIjqRkZPoB4Qzi/P/UZTuVqYtXgsLKz5MwN+6twVhGsicAu27s48q4xLDKC1AEx3De688UOBUEQhPaJhEzoV8qa6jFo9OhUGqqtDdhkJ6frSvn00llPm8NVhQAcrLzQRi/tC1UbKLX1vmRMo1Lx2MSbuGPIYJ835hUEQRA6TiRkQr/R5LTz0vGdOFxOJCRcXVikIkgKAqxd1n9X0KpU/GLKZG6KGxDoUARBCBC5thrbyWMozU1IwQb0aemoo8TUhe4gEjKh3yhvMmF3OQFQurhiWJ1sYlBYNCXmxi69jj89NXmiSMYEoZ9y5J+j8X//hu3oVy33tlSr0d88iZC7H0A7VExh6EqiwJAgdAEZmbgIdfsNe4gHx48jY9DAQIchCEIAWA/vp+b5FdgOH7h+o3FZxnb4ADXPr8B6+IDfr71q1SokSWrxiI+P9zy/ZcsWZsyYQUxMDJIkeTYFv5bNZuPxxx8nJiYGo9HI3LlzKSkpadFmzZo1ZGZmYjAYiIiIaDWWoqIi5syZg9FoJCYmhieeeAK7/erUk9ZilSQJo9Hol++FSMiEfmOgMRK9qvsGha30ji2UJg1M4J5RYjsUQeiPHPnnqP/Di9DeXpYOB/V/WIcj/5zfYxg3bhxlZWWex8mTJz3PWSwWsrKyWLduXZvnL1u2jK1bt7J582b27dtHY2Mjs2fPRr4mubTb7cybN4/HHnus1T5kWWbWrFlYLBb27dvH5s2b+eCDD1i+fLmnzYoVK1rEWVZWxtixY5k3b54fvgvilqXQj+jVGm4dMIR95ee75Xr1spmbkxIoqLJSZ7V1yzU7YvrQIWICvyD0U43/+7f2k7ErHA4a//fvRD71rF9j0Gg0LUbFrrVo0SIACgsLW33eZDKxfv163n77baZNmwbApk2bSEpKYvfu3cyYMQOA559/HoANGza02s/OnTs5c+YMxcXFJCYmAvCb3/yGJUuWsGbNGsLCwggJCSEkJMRzzvHjxzlz5gxvvPGGz6+5NWKETOhXqq3dO6erwlVGaLSJqOCgbr2uLwaFhQY6BEEQAkCurcaWfcinc2xHDyHXVvs1jry8PBITE0lJSWHBggXk5+d7fW52djYOh4Pp06d7jiUmJpKamsqBA97fYj148CCpqameZAxgxowZ2Gw2srOzWz3nT3/6EyNHjmTKlCleX+dGREIm9CtFjbXdfk0ZF/GhPTchC9XpAh2CIAgBYDt5DFw+Fq+WZeynjvkthkmTJvHWW2+xY8cO3nzzTcrLy8nMzKSm5vqi260pLy9Hp9MRGRnZ4nhcXBzl5eVex1FeXk5cXFyLY5GRkeh0ulb7sdlsvPPOOyxdutTra7RHJGRCvzI0NDDLt9VBTQG5rjf0mt6z+EAQBP9Rmjv2d8nVwfNaM3PmTO677z7S0tKYNm0aH330EQAbN27sVL+Kovg8FaO19m31s2XLFhoaGnjwwQc7HOO3iYRM6FeGhsUG5Loqp39W4XQFm1Nuv5EgCH2OFGzo0HmqDp7nDaPRSFpaGnl5eV61j4+Px263U1dX1+J4ZWXldSNe7fXz7ZGwuro6HA5Hq/386U9/Yvbs2W3OfesIkZAJ/cqA4LBuv2aYOpTjpXXtNwyQk5VVgQ5BEIQA0Kelg9rHEXK1Gl1qetcEhPtW4NmzZ0lISPCq/cSJE9FqtezatctzrKysjFOnTpGZmen1dTMyMjh16hRlZWWeYzt37kSv1zNx4sQWbQsKCvj888/9ersSxCpLoZ8ZE5FAmDYIs6P7quibnA3cPCiRoyX13XZNX2w4fopYQzApkRGBDkUQhG6kjopBf/Mkd/0xL+lvnuzXyv0rVqxgzpw5DB48mMrKSlavXo3ZbGbx4sUA1NbWUlRURGlpKQC5ubmAe0QrPj6e8PBwli5dyvLly4mOjiYqKooVK1Z4boFeUVRU5OlLlmVPPbPhw4cTEhLC9OnTGTt2LIsWLeKll16itraWFStW8OijjxIW1vKD/J///GcSEhKYOXOm374PIEbIhH5Gr9awZFRWt15TkqBJMnfrNX1R1mjh6V17yC7zfgKsIAh9Q8jdD4BW611jrY6Qu+f79folJSUsXLiQUaNGce+996LT6Th06BDJyckAbNu2jfT0dGbNmgXAggULSE9Pb1Fq4pVXXuGee+5h/vz5ZGVlYTAY2L59O+prRv+ee+450tPTWblyJY2NjaSnp5Oens6RI0cAUKvVfPTRRwQFBZGVlcX8+fO55557ePnll1vE63K52LBhA0uWLGnRvz9IiqJ07R4y3cRsNhMeHo7JZLoumxWEa7kUF//3q/exys5uu6aigMscQ3ljz53cPzQinJfvul3UJBOEHupG73NWq5WCggJSUlIICvJtVbf18AHq/7DuxvXItFoifvozgm71/jag4Obtz0aMkAn9zqGK/G5NxsA9ShYSYSEhpOsmw3ZWfr2J98+ew/HtrVMEQejTgm7NJHrly+hvzbp+Tplajf7WLKJXviySsS4m5pAJ/YpNdvKPopPtN+wCzUozCVFhlPXg/cbfPXWWZoeTB28aF+hQBEHoRtqhI4l86lnk2mrsp47ham5CFWxAl5ru1zljQttEQib0K9svHsfsaA7Y9RV8LMIYAJ8WXmRIRBhZSYNQq8TtS0HoT9RRMQTfdlegw+iXxC1Lod9wuGS+KPP/xri+kOj5CY7ZZueVr7J5audnnKgQJTEEQRC6g0jIhH7D6XLhIsBrWJTeUxW/2NzAyr37ySmvDHQogiAIfZ5IyIR+Q1YCPFldkaio797FBP7wt9PfBDoEQRCEPk8kZEK/oQBBai/r7fj72grEksilBktArt9RQRoNs0YMDXQYgiAIfZ5IyIR+I1QbxBOpU9Gquvm2oQKxDCSnB2+f1JbF48fx3cGDAh2GIAhCnydWWQr9yuCQKL4/KJXtRce77ZoxykCOl/W+ZAygsqnnFrIVBMH/XKZqXLlHUWwWJL0R1aibUYWLshfdQSRkQr9z58DRHKg4T42t628fxqnjOHqpdyZjANvPXSBjUCIjoiIDHYogCF1ILj6H89O/Ip8+BK5r5tuq1KjHTUYzdSHqpJGBC7AfELcshX5Hq1KTHjO4y68Tp4rnaFFDl1+nKzldLn5z8DB2Ub1fEPos58l92P7wFPLJ/S2TMQCXjHxyP7Y/PIXz5H6/X3vVqlVIktTiER8f73l+y5YtzJgxg5iYGCRJ8mwKfi2bzcbjjz9OTEwMRqORuXPnUlJS0qLNmjVryMzMxGAwEBER0WosRUVFzJkzB6PRSExMDE888QR2u71Fmx07djB58mRCQ0OJjY3lvvvuo6CgoNPfBxAJmdBPBat1Xdq/UTKQU9K7k7ErKixNmG22QIchCEIXkIvPYd+0Fpw32McSwOnAvukF5GL/13IcN24cZWVlnsfJk1d3U7FYLGRlZbFu3bo2z1+2bBlbt25l8+bN7Nu3j8bGRmbPno18zQdJu93OvHnzeOyxx1rtQ5ZlZs2ahcViYd++fWzevJkPPviA5cuXe9rk5+dz9913c+edd5KTk8OOHTuorq7m3nvv9cN3QdyyFPopm6udPz6dFKIKxaX0jYRsxrAhxBh67h6cgiB0nPPTv7afjHkaO3B+uhn1kuf8GoNGo2kxKnatRYsWAVBYWNjq8yaTifXr1/P2228zbdo0ADZt2kRSUhK7d+9mxowZADz//PMAbNiwodV+du7cyZkzZyguLiYxMRGA3/zmNyxZsoQ1a9YQFhbG0aNHkWWZ1atXo1K5x7NWrFjB3XffjcPhQKvt3Cp+MUIm9Et1tq6drC47+s5nnYXjxgQ6BEEQuoDLVI18+qBP58inD+IyVfs1jry8PBITE0lJSWHBggXk5+d7fW52djYOh4Pp06d7jiUmJpKamsqBAwe87ufgwYOkpqZ6kjGAGTNmYLPZyM7OBuCWW25BrVbzl7/8BVmWMZlMvP3220yfPr3TyRiIhEzopwobarqs72h1FCd76arK1hSZzYEOQRCELuDKPQouH/fXdcm4zh31WwyTJk3irbfeYseOHbz55puUl5eTmZlJTY13f6PLy8vR6XRERrZceBQXF0d5ebnXcZSXlxMXF9fiWGRkJDqdztPPkCFD2LlzJz//+c/R6/VERERQUlLC5s2bvb7OjYiETOh3rE4H1dauu51oadT1gi3EvffqV9mUN/augraCILRP6eBKc8XqvzsMM2fO5L777iMtLY1p06bx0UcfAbBx48ZO9asoCpLk297BrbW/tp/y8nIeeeQRFi9ezOHDh9m7dy86nY77778fRen8tnwiIRP6nRJLXZftaGlQGSio7VsjSjXNVn7+2Zd8U911o4qCIHQ/SW/s2HlBXTen1Gg0kpaWRl5enlft4+Pjsdvt1NW1vCtRWVl53YhXe/18e0Strq4Oh8Ph6eePf/wjYWFh/PrXvyY9PZ3bbruNTZs28emnn/LVV195fa22iIRM6HeKLbVd1neYFN6nRseuqLNa+cXn+zhZWRXoUARB8BPVqJvB151LVGpUI2/umoBwl7A4e/YsCQkJXrWfOHEiWq2WXbt2eY6VlZVx6tQpMjMzvb5uRkYGp06doqyszHNs586d6PV6Jk6cCEBTUxNqdcvv15WvXb7e+m2FTwnZ66+/zvjx4wkLCyMsLIyMjAw+/vhjz/Pe1Av5tjfffJMpU6YQGRlJZGQk06ZN4+uvv/b5hQiCt0aExaGWuuaziCz33c84LkXhg7PnuFBbH+hQBEHwA1V4DOpxk306Rz0uw6+V+1esWMHevXspKCjgq6++4v7778dsNrN48WIAamtrycnJ4cyZMwDk5uaSk5PjGc0KDw9n6dKlLF++nE8//ZRjx47x4x//2HML9IqioiJycnIoKipClmVycnLIycmhsbERgOnTpzN27FgWLVrEsWPH+PTTT1mxYgWPPvooYWFhAMyaNYvDhw/zq1/9iry8PI4ePcpDDz1EcnIy6enpnf5e+PTuMWjQINatW8eRI0c4cuQId955J3fffTenT58GvKsX8m179uxh4cKFfP755xw8eJDBgwczffp0Ll265NsrEQQvDQqJZPbg8V3St0rt7JJ+e4rBYWEMiQgPdBiCIPiJZupC0Hi5QlCjQzN1gV+vX1JSwsKFCxk1ahT33nsvOp2OQ4cOkZycDMC2bdtIT09n1qxZACxYsID09HTeeOMNTx+vvPIK99xzD/PnzycrKwuDwcD27dtbjGY999xzpKens3LlShobG0lPTyc9PZ0jR44A7pGujz76iKCgILKyspg/fz733HMPL7/8sqePO++8k3fffZcPP/yQ9PR0vv/976PX6/nkk08IDg7u9PdCUjo5Ey0qKoqXXnqJpUuXeo4VFhaSkpLCsWPHmDBhgk/9ybJMZGQkf/jDH3jwwQe9Ps9sNhMeHo7JZPJks4LQlosNNbx0Yoff+1UUCLEncK7a5Pe+e4L/mTWdWOPV+SPljRb+ePgYNyfE8cPRIwIYmSD0fTd6n7NarRQUFJCSkkJQUJBP/TpP7se+6YUb1yPTaNH9+Odo0rI6Enq/5u3PpsP3V2RZZvPmzVgsFjIyMjrazXWamppwOBxERUX5rU9B+DaNr/MmvCRJoASbMGj7Th2ya318vgC7LPP83gOYbTZWf3mQU1XVfJibx99Of0O9VVT0F4TeRpOWhf6nr6BO++71c8pUatRp30X/01dEMtbFfH7XOHnyJBkZGVitVkJCQti6dStjx471W0A/+9nPGDhwYIt7v62x2WzYrtnOxSxqJQk+CNP69gnSF02uJkbHJ3C0uO+Nkv0j7wIWh4OcikrW7vuKSw3u+Rdmm53Np7+htKGRpybfEuAoBUHwlTppJOolz+EyVeM6dxTF2oQUZEA18ma/zhkT2uZzQjZq1ChycnKor6/ngw8+YPHixezdu9cvSdmvf/1r/vrXv7Jnz552h1zXrl3r2QpBEHyldFnhC7cqVwVh+jDMNnv7jXsRh8vFzvxCAL6puX616hdFJcSFGHlg7GjUKt9qAAmCEHiq8BhUt05vv6Hgdz7fstTpdAwfPpxbbrmFtWvXctNNN/Hqq692OpCXX36ZF154gZ07dzJ+fPsTrp955hlMJpPnUVxc3OkYhP6j2NK1lfRduAjXd+0G5j3Ve2dyeSM7xy+FEgVBEPqLTk90URSlxa3DjnjppZdYvXo1O3bs4JZbvLvdodfr0ev1nbqu0D81O+38/cLhLr9ORISdAeHhFNbYqGmydvn1epLdBReJDzFy35iRgQ5FEAShV/ApIfv5z3/OzJkzSUpKoqGhgc2bN7Nnzx4++eQTwF0vpKioiNLSUsBdLwTcFXCv7OT+4IMPMnDgQNauXQu4b1P+8pe/5N1332XIkCGe2iIhISGEhIT451UKwmUuReHtvEPUdHDLEF/UyvVAPfExYZhLVDj8UDiwN3n/bC4zh6dg8MOmu4IgCH2dT7csKyoqWLRoEaNGjWLq1Kl89dVXfPLJJ9x1112Ad/VCioqKWlTC/a//+i/sdjv3338/CQkJnse1tT8EwR/M9mb+krufE7Ul3XrdetnM+IGh3XrNnsDqlFm7/yv+knOSZkffrs8mCILQWZ2uQ9ZTiDpkwo1UWxt5Pnt7l0/mb4uiQLgzkbOV9QG5fqA9mj6eH4wYGugwBKFX66o6ZELX8vZn0zeLJQnCt1Q1NwQsGQN3fTKLtoIIfRj1nZxz2Ru9c+oMGYMSiQwWbxSC0JMpjbUoJSdQ7M1IumCkQeORQkRd0O4gEjKhX6i0Br5OnYxMTKyVFCWS81UW7LILl6L0i7llTQ4nJyuruC05KdChCILQClflBVxHt6JcPAou+eoTKjVS8s2obv4hqgHDAhdgP9B3d0IWhGsUNtQEOgQAmpVmKiklLMZMdFwDowf0j30hI4P03JIYH+gwBEFohSv/a+QPV6IUHG6ZjAG4ZJSCw8gfrsRV4P/V6atWrUKSpBaPK4sAAbZs2cKMGTOIiYlBkiRycnKu68Nms/H4448TExOD0Whk7ty5lJS0nCu8Zs0aMjMzMRgMREREtBrLk08+ycSJE9Hr9a1u+7hnzx7uvvtuEhISMBqNTJgwgXfeeaczL78FkZAJfZ7Z3syJmu6dyN8uSUGSoNHWPya73zFksFhtKQg9kKvyAvLu10C+wT6WALIDederuCov+D2GcePGUVZW5nmcPHnS85zFYiErK4t169a1ef6yZcvYunUrmzdvZt++fTQ2NjJ79mxk+WpyabfbmTdvHo899lib/SiKwsMPP8wDDzzQ6vMHDhxg/PjxfPDBB5w4cYKHH36YBx98kO3bt3fgVV9P3LIU+rythcewuXpe4hMsBXGhriHQYXSL6ODgQIcgCEIrXEe3tp+MXSE7cB39ENX3l/s1Bo1G02JU7FqLFi0CoLCwsNXnTSYT69ev5+233/Zsubhp0yaSkpLYvXs3M2bMAPDs7LNhw4Y243jttdcAqKqq4sSJE9c9//Of/7zF10888QQ7duxg69atzJkzp+0X6CUxQib0ec3Onrl9UYgrOoDLDLrXR+fzsdh75s9BEPorpbEWpTDbt3MuZqM0Xr9tWmfk5eWRmJhISkoKCxYsID8/3+tzs7OzcTgcTJ9+dbunxMREUlNTOXDggF/jbI3JZCIqyj+LHkRCJvRpX5blcaquNNBhtMrZ9+fye5Q2NPKX46cCHYYgCNdQSk6A4uMfIpeMUnKy/XZemjRpEm+99RY7duzgzTffpLy8nMzMTGpqvJv3W15ejk6nIzIyssXxuLg4T6H5rvL+++9z+PBhHnroIb/0JxIyoc8qbKjm7/ldv0VSR1k1NUT1ozIQnxcWY7F7eWtEEIQup9ibO3aeo8lvMcycOZP77ruPtLQ0pk2bxkcffQTAxo0bO9WvoihIkuSPEFu1Z88elixZwptvvsm4ceP80qdIyIQ+yemS+e+zX/ToW4LNipXBA/rPP0GXopBX27WbuguC4D1J17G5nZLW4OdIrjIajaSlpZGXl+dV+/j4eOx2O3V1Lf+2VFZWEhcX1xUhsnfvXubMmcNvf/tbHnzwQb/123/eDYR+pcraQIOj52/oLSld9wmuJ9pdcDHQIQiCcJk0aDyo1L6dpFIjDUrrmoBwl7A4e/YsCQkJXrWfOHEiWq2WXbt2eY6VlZVx6tQpMjMz/R7fnj17mDVrFuvWreMnP/mJX/sWqyyFPqnUYgp0CF5RpJ48hud/+4svMXfkcEZGR7bfWBCELiWFRCEl3+yuP+btOckT/Vq5f8WKFcyZM4fBgwdTWVnJ6tWrMZvNLF68GIDa2lqKioooLXXPBc7NzQXcI2Px8fGEh4ezdOlSli9fTnR0NFFRUaxYscJzC/SKoqIiT1+yLHvqmQ0fPpyQkBAAzp8/T2NjI+Xl5TQ3N3vajB07Fp1O50nGnnzySe677z7PHDWdTueXif0iIRP6pMNVBYEOwStm2YxGpcPZD6r1X3GsvEIkZILQQ6hu/iFyUY53pS/UWlQ33+PX65eUlLBw4UKqq6uJjY1l8uTJHDp0iOTkZAC2bdvWYtL8ggULAFi5ciWrVq0C4JVXXkGj0TB//nyam5uZOnUqGzZsQK2+Ovr33HPPtZiXlp6eDsDnn3/O7bffDsAjjzzC3r17r2tTUFDAkCFD2LBhA01NTaxdu5a1a9d62n3ve99jz549nf5eiM3FhT6nrMnEupyPkX1dPRQgYfZEzlbVBzqMbqGS4KVptzM0MiLQoQhCr9NVm4u7Cg4j73r1xkmZWov6ridRpdzakdD7NW9/NmIOmdCnyIqLTXkHe00yBqAP7j8rD+eOHC6SMUHoYVQpt6K+53mklO9cP6dMpUZK+Q7qe54XyVgXE7cshT5l96WzXPRz0cKuVuWsYkxsIiUmCw19vCzE8Yoq/nb6GzIGJTI4XIxkC0JPoRowDNX3l7uLxZacRHE0IWkNSIPS/DpnTGibSMiEPuNsXRnbLx4PdBi+k8CsKyU5PoJTRYEOpmsV1JuIMQQzNSU50KEIgtAKKSQKafT3Ah1GvyRuWQp9Rk5NcaBD6JRaZz0TEvv2ZPfo4GD+/ZZ0wvX6QIciCILQo4iETOgTvqkv51Cl9/uf9USSBFXSJSYM7LtJWb3Vyr9+tINCU+8oSyIIgtBdREIm9AmXLHW9aiL/jahUfeN1tEZWFOyyi/XHTtLscAY6HEEQhB5DJGRCnzAhOinQIfiN7Oz7/yxza2p5csen7M6/iNyParAJgiC0pe//5Rf6hSi9kRBt35iX1CcKA3qhqqmZPx45xosHvg50KIIgCAEnVlkKfcLHxadodNgCHYZfNKlrGBgayqUGC2F6HYoCDXZ7oMPqMvEhxkCHIAjCZYq1DqrPgtMKmiCIGYMU1HfntfYkIiETer0TNSX8s/hkoMPwm2bFihJqZWi4DoNKh6w4KanQ9tkaZR+fL2B4ZAS3Jfed286C0Nso9RdRLnwMlSfg2vm4kgplwHikYTORIkS5mq4kblkKvV5vL3dxhaRIqFAxQD2AYGs8xaU6ThXZOVvs6rPJGIDT5eKVr7L5n6PHkV395YatIPQcSvkxlEMvQUVOy2QM3F9X5KAcegmlPMfv1161ahWSJLV4xMfHe57fsmULM2bMICYmBkmSPBt+X8tms/H4448TExOD0Whk7ty5lJSUtGizZs0aMjMzMRgMREREtBrLk08+ycSJE9Hr9UyYMOG653Nzc7njjjuIi4sjKCiIoUOH8uyzz+Jw+Ofvs0jIhF4vQm8IdAidNkA9AFN1GMWXgjhW1MiFWjOOfjbZ/ePzBTz/xX52XijE0ocTUEHoSZT6iyg568HVzqpnlxMl508o9Rf9HsO4ceMoKyvzPE6evHrHw2KxkJWVxbp169o8f9myZWzdupXNmzezb98+GhsbmT17NrIse9rY7XbmzZvHY4891mY/iqLw8MMP88ADD7T6vFar5cEHH2Tnzp3k5ubyu9/9jjfffJOVK1d24FVfT9yyFHq9YLU20CH4JFodxfkyJwPDjIToVZiaZY7VmQMdVo9wsrKak5XVyIqLmcOHBjocQejzlAsft5+MXeFyolz4BGniv/o1Bo1G02JU7FqLFi0CoLCwsNXnTSYT69ev5+2332batGkAbNq0iaSkJHbv3s2MGTMAeP755wHYsGFDm3G89tprAFRVVXHixInrnh86dChDh179u5ScnMyePXv48ssvb/wCvSRGyIRez2RvDnQIPmlWrEhI5NWYOFZaR75Ixq7zt9O5/Hf2cb6prgl0KILQZynWOvecMV9UHnef50d5eXkkJiaSkpLCggULyM/3vsh3dnY2DoeD6dOne44lJiaSmprKgQMH/Brnt50/f55PPvmE733PP1tNiYRM6NWcLpkTtSXtN+xBmlxNDE5wkRweihToYHook83GJxcKWP3lIZz97NatIHSb6rPXzxlrj+KC6m/8FsKkSZN466232LFjB2+++Sbl5eVkZmZSU+Pdh7Hy8nJ0Oh2RkS1XgsbFxVFeXu63OK+VmZlJUFAQI0aMYMqUKfzqV7/yS78iIRN6te0XT1BrswQ6DJ+Z5QacIRWkJ4UHOpQezeJwiMKxgtBVnNbuPa8VM2fO5L777iMtLY1p06bx0UcfAbBx48ZO9asoCpLUNR95//a3v3H06FHeffddPvroI15++WW/9CvmkAm91vGaYj4tPRvoMDpHEqsKbyQxNAS9RvyZEoQuoQnq3vO8YDQaSUtLIy8vz6v28fHx2O126urqWoySVVZWkpmZ2SUxJiW5S/SMHTsWWZb5yU9+wvLly1Gr1Z3qV4yQCb2SwyXzfkF2oMPoNBtNgQ6hRytvbCSnvDLQYQhC3xQzBiQf0wBJBTGjuyYe3CUszp49S0JCglftJ06ciFarZdeuXZ5jZWVlnDp1qssSsmspioLD4UBROv/hWnz0FHqlryoLqLP1/mSmzmkmRBdOoyjz0CqXAqu/PMgvb8vgprgBgQ5HEPoUKSgSZcB4d/0xbw24ya+V+1esWMGcOXMYPHgwlZWVrF69GrPZzOLFiwGora2lqKiI0tJSwF0LDNwjY/Hx8YSHh7N06VKWL19OdHQ0UVFRrFixwnML9IqioiJPX7Ise+qZDR8+nJCQEMA9Sb+xsZHy8nKam5s9bcaOHYtOp+Odd95Bq9WSlpaGXq8nOzubZ555hgceeACNH0byRUIm9DouRWFXyelAh+EXkgQpUSGcLPfvqqW+RFYUPsrLFwmZIHQBadhMlKpT3pW+UGmRhn3fr9cvKSlh4cKFVFdXExsby+TJkzl06BDJye5dAbZt28ZDDz3kab9gwQIAVq5cyapVqwB45ZVX0Gg0zJ8/n+bmZqZOncqGDRta3EJ87rnnWsxLS09PB+Dzzz/n9ttvB+CRRx5h796917UpKChgyJAhaDQaXnzxRc6dO4eiKCQnJ/Mf//EfPPXUU375XkiKP8bZegCz2Ux4eDgmk4mwsLBAhyN0IUVR+O+zX3Cq7lKgQ/GLGHU0x4t6V+mOQPhu0kCWpqcREdR181cEoSe70fuc1WqloKCAlJQUgnz8N6KU56Dk/OnGSZlKgzThEaT4CR2IvH/z9mcjRsiEXkeSJP51zG3kmSp55/whanrhKstrVTtruClxIMdLxSjZjewrvsTxiipmDk9hXGwMcUYDUcHBaNViKqwgdIYUPwEm/x+UC59A5fHr9rJkwE1Iw74v9rLsYiIhE3olSZIYGRHH3UMm8Ofc/YEOp3MkqOYSw6PiOV8risTeSIPdzt/P5ALueSQqCVIiInj5rtsDGpcg9HZSRDLSxH91F32t/sZd2kITBDGj/TpnTGibSMiEXi1Sbwx0CH5j0HVuyXR/5FJg/IDYQIchCH2GFBQJgzICHUa/JMb6hV5N4+uS7Z5KkSgxiXlkHRFjCA50CIIgCJ3WR97NhP4qOiikT2w/FKOJprbZf9Wv+5Mt35zjy6ISXH1jfZIgCP2UTwnZ66+/zvjx4wkLCyMsLIyMjAw+/vhjz/NbtmxhxowZxMTEIEmSp4ZHez744APGjh2LXq9n7NixbN261acXIfRfBo2OoWG9/5aVjEN8OuqgmmYrvz10hCc++ZQPzp6jytL769MJgtD/+PQeMGjQINatW8eRI0c4cuQId955J3fffTenT7trQlksFrKysli3bp3XfR48eJAHHniARYsWcfz4cRYtWsT8+fP56quvfHslQr810Nj7J5zWySaxr2UnXWpoZNPJM/zko52s3LNfjDgKgtCrdLoOWVRUFC+99BJLly71HCssLCQlJYVjx44xYcKEG57/wAMPYDabW4y0ff/73ycyMpK//vWvXsch6pD1X9suHmdnHygUqygQ4UzkTGV9oEPpE9LjB/CvN99Eg93O8Kjen7QLQlfVIRO6lrc/mw7fJZFlmc2bN2OxWMjI6PiKjIMHDzJ9+vQWx2bMmMGBAwc63KfQv1jlvrHtkCSBSVPKhGQD+k5uUivAsfJK/u2fu/g/u/fyyfmCQIcjCL2C4jCj1B5DqTrk/q9DlOLpLj6XvTh58iQZGRlYrVZCQkLYunUrY8eO7XAA5eXlxMXFtTgWFxdHeXn5Dc+z2WzYbDbP12az+KXpj1yKizxTRaDD8B8JqpzVDIlMILfaFOho+oz3z57ju4MHEqLTBToUQeiRlKZLUPklmHKBawrDokIJHwUDpiAZBgYqvH7B5xGyUaNGkZOTw6FDh3jsscdYvHgxZ86c6VQQktRynZyiKNcd+7a1a9cSHh7ueSQlJXUqBqF3OlxVSFlT30tcDAY50CH0KTXNzfzp2IlAhyEIPZJiOgvn/wyms7RMxnB/ffl5xXTW79detWoVkiS1eMTHx3ue92axoM1m4/HHHycmJgaj0cjcuXMpKSlp0WbNmjVkZmZiMBiIiIhoNZYnn3ySiRMnotfr251udf78eUJDQ9vsqyN8Tsh0Oh3Dhw/nlltuYe3atdx00028+uqrHQ4gPj7+utGwysrK60bNvu2ZZ57BZDJ5HsXFxR2OQei9cmr65s+9yllFnNEQ6DD6lK8v3XjUXRD6I6XpElx8H5R2NhdXnHDxfXd7Pxs3bhxlZWWex8mTJz3PebNYcNmyZWzdupXNmzezb98+GhsbmT17NrJ89YOt3W5n3rx5PPbYY232oygKDz/8MA888MAN43U4HCxcuJApU6b48Crb1+lK/YqitLh16KuMjAx27drVYrf0nTt3kpmZecPz9Ho9er2+w9cV+oZqa2OgQ+gSiqSQGC1R0bu36exRQnTaQIcgCD1P5ZftJ2NXKE53+yEL/BqCRqNpMSp2rUWLFgHuxYKtMZlMrF+/nrfffptp06YBsGnTJpKSkti9ezczZswA4Pnnnwdgw4YNbcbx2muvAVBVVcWJE22PqD/77LOMHj2aqVOn+nW+u08jZD//+c/58ssvKSws5OTJk/ziF79gz549/Mu//AsAtbW15OTkeG5h5ubmkpOT02IE7MEHH+SZZ57xfP3kk0+yc+dOXnzxRb755htefPFFdu/ezbJly/zw8oS+LqkPlLxoS4OrgRHR4UQGiQ8e/lBvtVHTJHZDEIQrFIf58pwxH5hy/T7RPy8vj8TERFJSUliwYAH5+flen5udnY3D4WixODAxMZHU1NQuWRz42Wef8d577/HHP/7R7337lJBVVFSwaNEiRo0axdSpU/nqq6/45JNPuOuuuwDYtm0b6enpzJo1C4AFCxaQnp7OG2+84emjqKiIsrIyz9eZmZls3ryZv/zlL4wfP54NGzbwt7/9jUmTJvnj9Ql93E3RfXfuYLNipSmojCHRYmsgf3C4XHxZVNJ+Q0HoLxoucP2csfa4oMH7hKk9kyZN4q233mLHjh28+eablJeXk5mZSU1NjVfnl5eXo9PpiIxs+eHcm8WBvqqpqWHJkiVs2LChS8pr+XTLcv369Td8fsmSJSxZsuSGbfbs2XPdsfvvv5/777/fl1AEAYBBxkgkoC9vmlNUKwqc+kuxuSHQIQhCzyF3cLqR7L+/STNnzvT8f1paGhkZGQwbNoyNGzfy9NNPd7hfbxYH+urRRx/lRz/6Ebfddptf+72i03PIBKG7yYqL1059SmFDDbLi66e73iciWEeNqDrvFyNEgVhBuErdwekQ6q4rPGs0GklLSyMvL8+r9vHx8djtdurq6lqMklVWVrY7F91Xn332Gdu2bePll18G3Emfy+VCo9HwP//zPzz88MOd6l9snyf0OqdrS7lgruoXyRiAQde3i8QGadQMD+/6FaVheh3ThiZ3+XUEodcIHYbvaYAKQod2RTSAu4TF2bNnSUhI8Kr9xIkT0Wq17Nq1y3OsrKyMU6dO+T0hO3jwIDk5OZ7Hr371K0JDQ8nJyeGHP/xhp/sXI2RCr6EoCudMFfz1wteBDqVbROsNWGUnmr58PxZ4NNnBbeps5psmdOmt5wEGAxqV+AwqCFdI2jB30Vdf6ouFj0LS+m/+1IoVK5gzZw6DBw+msrKS1atXYzabWbx4MeBeLFhUVERpaSngXiwI7pGx+Ph4wsPDWbp0KcuXLyc6OpqoqChWrFhBWlqaZ9UluOevX+lLlmVPPbPhw4cTEhICuGuLNTY2Ul5eTnNzs6fN2LFj0el0jBkzpkXsR44cQaVSkZqa6pfvhUjIhB6v2WlnX/l5DlXmU9HcP3ZkCNcFsWSkHb3Gzs48hWOBDsjP5gwKJl5rJVTl4Lsad82hibEhHKnqujImRlH2QhCuN2AKmPO8K30hadzt/aikpISFCxdSXV1NbGwskydP5tChQyQnu0ezt23bxkMPPeRpv2CBu+TGypUrWbVqFQCvvPIKGo2G+fPn09zczNSpU9mwYQPqa7age+6559i4caPn6/T0dAA+//xzbr/9dgAeeeQR9u7de12bgoIChgwZ4tfX3ZpOby7eU4jNxfsmu+zkj2c+54K5KtChdKvFI8NJCa32fH2iPJ4/Hrbi6gP/XO9KNPBY6P7rjrsU+NgxkbcuuldE+tvdI4ezZIJ/PskKQiB01ebiiuls+8VhJQ0k348UPqbtNkKrunxzcUHoag12K//zzRf9LhkDiNI1tfh6fHw5S9N7f+X+WYOCeTTkYKvPqSSYpcvm8RS7368bHRzMA+NG+b3fXkFxgVwCjuMg979/S0L7pPAxMPxhCB/D9WmByn18+MMiGeti4pal0CPtKc3lfy/m4HD1zz0dz5nDuTW2ZVL2nUGl6NUJvHGkGVlRSBsQhkErcehSz9/LUwLWjahhhKqo3bYZ6lPEGydTbvHfytKHJqQSrO2HtyzlKnDkAJe/l3IROCNBkwxSNKh6f5Iv+IdkGAhDFriLvjbku0tbqIMgdKhf54wJbRMJmdDjVFsbeb8gO9BhBJS5jUGimxLKWDvNgEuRiDK49/GcnBTHG0ccWJ09L3lNDjOgV0l8J9zuVTIGoJYUBhk0lPtp26jHJk4gK2mgfzoLNLnKPdqlHQeSDhQZXKUgXwJXHaiiQRUFisV9+8lVen0fSh046tz/rxkN6uHg53pNQu8lacMgakKgw+iXREIm9DifXvJhxU8fFaVve65YRHDLkbNxAyp49rYwNhwL5Xzd1Unxo6JDCdZI2GQFs02mrLG5S+egfWdACKFqhRHBFgar69jbNJDJhkpuUnlXT+haww12jvghpvT4AUwfNsQPPQWI4nTP3fF8bQJXCTgUUIWAswi4ZjsoV4X74S3nN+CqBXUySAZQhcGV3xGRpAlCtxIJmdBj2GQHb+Ud4nhNcaBDCbgmp29vhnEhZhakalj9pfvrIRFGVmS13CaotsnI309Hk13m/1ucPx6i5V79ly2OjQ4p7HB/I7R1gLFzQQHVvXnvSrnKPe9Le5N71EtSg+vyKmPXJd93vGmLq9L9AJDCABlUCaAV84UEoTuJhEzoMQ5XXRTJ2GVn6mxkxft2jk4jo1OpsLtcDIu8fr5UlMHCv91qwerQYJc1VFhC+SQviBOVHS8lEmcI4omB5YxRFXS4j9Y0o+vU+QNDQ7A6nah76yiPXAqOo4ACjkOgSQX14KuJU1dRLv8uyPmgHugeMRMEoVuIhEzoMRwuL+rg9BMVzRYUxbe7RgmhJl6arqXeaiA+9GKb7YK0ToK0TsKCrIyIhvrmYBwuDdEaLbvOavi4TMbi8O5nkRGN35MxALNLR2d2KB0bG81jEyf4LZ5u5aq9mox5jl3ZJNnRXUGA/cDl0bl4cftSELqBSMiEHqMPlNjym+Hh4UiS76MhBp0Dg863W5IRwVdv6903RMsDQeeoIJYQmgihkSYMVBDNweZBfFTqwCZfXTxgkbumcs4dmpMcjZ3EkaqOzez/tKCI2wYPInVArJ8j6wbOAq5LRl3V7ke3coDjCKhTQCvqtwlCVxMJmdBj5JrK22/UD6RFRjFzcF1Art0Y4SQoeAIxjQ1oTI2oHFxOzJoYZihm1rAwtjSlkhZUx2FLNJlGHyaQ+0AvOfh51D6ORoziw5pYmmWFGquTept3Ncr0ahV/O3WGcXfchiRJKHUnoforGDQHKTiuS2L2C8UVgMSrHXKBe5RMHRPoSIRuoMiNYCsBxe5eyasfhKQOCXRY/YJIyIQeocFu5WxdWaDD6BG+n1SPQeP/4qjeUbDqTVj1oIoeirHagq7m6i3JSMnMUuMBAL7TDdOLblblcnOse+86RYFvlBTO2GNRSwrxGgvJqio+bBzJrtImRkYYeWSA+1ZtHLWocNF8yU6wWgVV+90lIhrOw+WETFEUaCiBmnOg1kL0GCRjgEfUFBMQqJ/9DUi+VX4Xeh/FXgmN2WC7SMsVIyoUfTKETETSDQhUeP2CqNQv9AhFjTW4unRr6d7BqNFh0NgCHQYALppoiJEwjUjHGRL4P8SS5J6vdl/Q19yjP8xk9RkSpCoeC93PxlG5rB2wj+FSMcOlYkIlC0apmeCafVD5hTsZA3C4b+cqtloo2Y5y4EWUs++hnHoXZf8LKM21AXyFgNw1I46doop3l9gQ+izFmg81W8FWwPXLd13u4zVb3e38bNWqVUiS1OIRH391RdOWLVuYMWMGMTExSJLk2fD7Wjabjccff5yYmBiMRiNz586lpKTlKvM1a9aQmZmJwWAgIiKi1ViefPJJJk6ciF6vZ8KECdc9X1hYeF2skiTxySefdOZb4CESMqFHCNMFBzqEHmFMRGiPmz/tVJkwD4zEHj000KG0KZQm775v1YdRTv8avnkVarMh8pqCsc5mlJObUJze7RCgOG0osp8m2cvFoDSD3PZijIBRDw50BEIXUuyVULcLaK+wtAx1u9zt/WzcuHGUlZV5HidPnvQ8Z7FYyMrKYt26dW2ev2zZMrZu3crmzZvZt28fjY2NzJ49G/ma+a52u5158+bx2GOPtdmPoig8/PDDPPDAAzeMd/fu3S3ivfPOO314tW0TtyyFHmFAcBhqSYWs+H9T6d5gkDGUJqeTOwcGeISmDcZ60NX4/9Nx93OB85qFAk31LZ+uPoNy9n2ktB/fsBel/BjK8Q0Qnw6j74Pqs6A1oNTkQsMl93CeLhQpchgMnISkblnGQ1FcUHkKpeoUKArSwGgwgNRtqyh9IIntlfq0xmzaT8aukMFyFHTf92sIGo2mxajYtRYtWgS4R6daYzKZWL9+PW+//TbTpk0DYNOmTSQlJbF7925mzJgBwPPPPw/Ahg0b2ozjtddeA6CqqooTJ0602S46OrrNeDtDJGRCj6BXaxgQHEpZU8/fl7Er3BKrY3xULaoeNjrm0ReXwOpioPn09ceL96NEpCAlZQGgmIqg8gQYYlFq86CxFOour4S8dAjl0qE2L6FcOgS5H6IMnoI0bCaSRo/iklGO/wXKru5FoBQDg9JgZDJSj7t1L8rR9FXuCfyFvp1kLUSRG/060T8vL4/ExET0ej2TJk3ihRdeYOhQ70bks7OzcTgcTJ8+3XMsMTGR1NRUDhw44EnI/Gnu3LlYrVZGjBjBU089xf333++XfkVCJvQI502VlPfTZAzg42ITMfpIBhrretwtSwBLpAqUkeirzgU6FP/QDUApLWzjSQXl5NsolkokfShK3j/Ay9uYrXJY4MInKEVfQMp0lKaqFsmYR8lJSB4Jev9tqt5pUhRIoYGOQugqthJ8r/fncp9nGO2XECZNmsRbb73FyJEjqaioYPXq1WRmZnL69Gmio6PbPb+8vBydTkdkZGSL43FxcZSX+3flfkhICL/97W/JyspCpVKxbds2HnjgATZu3MiPf3zjUXVviIRMCLhmp4NN5w/1uHGB7mSTnfwpt5GHR0UzOKQm0OFcR8FOYxQ4Qm/GmH+UHpgzek+biFKQQ7tvRPk7/Ps76WhCOffhDZso5cVIyT2kdpoUArrJ7i2bhL5J6eCK3o6e14qZM2d6/j8tLY2MjAyGDRvGxo0befrppzvcr6IoSH7+dBsTE8NTTz3l+fqWW26hrq6OX//6135JyMSkfiGg6mwW/njmM6qtje037iWC1VoGBHVsH8bjNddvedSTKD1x+M4XuhiUwmN0ZheALlWQjUIPSYCkcJGM9XVSB7co6+h5XjAajaSlpZGXl+dV+/j4eOx2O3V1LWs3VlZWEhfX9TUHJ0+e7HWs7REJmdDtzhfXY7c7+WfRSX555H8pbOh5I0KdcV98EL9MvMSdsVFetQ/V6gG4LT6G7wxo6srQOkVCR8iFXj461tP/5LlkMMkoih5XYQWKHMDVx64ysO0Hxyn33pouk7twrdB36Afh+78J1eXzuobNZuPs2bMkJCR41X7ixIlotVp27drlOVZWVsapU6fIzMzsqjA9jh075nWs7RG3LIVuVVXXzIpX9pH1vSguxhQGOpwuUWDVMkkP94TkU21P4YSp9ar7k2JjuC2hBqO2EZusQa/u2YVxFexYhqYTkn800KF0Qs9PJ5Xsj67+/6WzKIYIpJsmI6m6e26ZC5RakGvd1frBfRtTexOovPuwIfRskjrEXfTV5sN+tEFD/Dqhf8WKFcyZM4fBgwdTWVnJ6tWrMZvNLF68GIDa2lqKioooLS0FIDfXXSg6Pj6e+Ph4wsPDWbp0KcuXLyc6OpqoqChWrFhBWlqaZ9UlQFFRkacvWZY99cyGDx9OSIj79Zw/f57GxkbKy8tpbm72tBk7diw6nY6NGzei1WpJT09HpVKxfft2XnvtNV588UW/fC9EQiZ0G9ml8NtNR7E5ZGqqHEQ2DMRhBfuIKuwBq0zvf+ctNpQwd+WDWRF1nDGrcLYysjAywoFR637denXPX8mmIpjgMv9vJN69etktOJsFbBaU6nqkAT2gWr7SCPaDoBoAqghQJYKqY7fnhR4iZCLYivCu9IUajDf79fIlJSUsXLiQ6upqYmNjmTx5MocOHSI5ORmAbdu28dBDD3naL1iwAICVK1eyatUqAF555RU0Gg3z58+nubmZqVOnsmHDBtTqq//en3vuOTZu3Oj5Oj09HYDPP/+c22+/HYBHHnmEvXv3XtemoKCAIUOGALB69WouXryIWq1m5MiR/PnPf/bL/DEASVH6xnp2s9lMeHg4JpOJsLBu2NNF8IlTdvHHv5/gkwPXF77UaVWk326gOroCRQGj04ALBau2uZWeeodlSTqGad0FFHMd8fzPJQd219U/eIOMoSwdVdsjV1S2RkUwYRcvobbWBzqUjtFGoFicUF14tWp/bxI/CtXY4YGOonWS0Z2YaUaC1MNvCfdyN3qfs1qtFBQUkJKSQlCQb8m7Ys33ojisGiLvQgrquQWieypvfzZihEzwq62fXaDGbCUhxkB8tJGIUD3ni+v5x5cFnC9uvayF3eHi/GEHgwYPpKLMRn5VM1qNmvE/iKTeEJhNtjvrkCWEYRHuhGyUtpx/GxjHH0pcuBQFjaTiB0muXpOMAUiKFlVvTcYAcEGT6WoyZoiEoDBoqADHNbcCB4yASv9M0PWr8nMoY0cheV3AsxspFpDzwFUDmsGABiQtoHff4uxNv+j9lBQ0FCX6h+6ir9ZCvr2XJUFDwHiz2Muyi4mETPALRVF49+NcNn2c26Hza+pt1NRf3cPR4XRRsFci4vsgKRBujcBkqPdTtF3v69o6poeGEas2AzBCW8GDSUNp1igkhZgI0dYHNkAfyZIZ68A0gi+dbL9xT+QwI0UbUTQ6pKgIsNcAVgiJR2lwQV0RUnI6OMtgSDq46kGlR7EqUN6x32m/GpXF9XsM9jBKLTi+tdOEZiyoh4qkrBeQdANA9/3LxWJL3KUtJB3oB/l1zpjQNpGQCZ2iKAr7j5execc5LpT4t7BrrcnGoDMDqam0c6GiiUkzBmA1WmjUWdo/OcBcKJx3RHgSMoCbNQWYIgcg0zM2D/dVc4gDVfwY1I01qBsre8H0+G+RrUgh0uVk7MqxZiSjBiJSwe6eNIzj8n/lJnfVh5RxKFWV0FjV7SEDMO4OVHEGemypjhtxngGXGXTpgY5E8JKkDvFb0VfBNyIhEzqssraJ375zjOPnqrvsGidO1nv+/6sdFnRaFUPu0SD3gknw3zRryLhmuoCEgt6pp0nTO2uuKdhpDAfCQ1ArCYQWF6Nu7pl7b7atlaRGcYL9BsmWvRopOgzF1tDy9mY3kWKigd47nxJXCbhGgerynpiKCxSzewcAUedMEDxEQib47N1Pctm2Nx9TY/evjLQ7XBgdBszXjDz1VPmWJmi5mwdaqwn6wOi/LDXQlDiE0Au9LSHrIGcj0qAxKAXHuv/avXBg7DquCpAS3PPMnN+A0uReCKCbGOjIBKHHEAlZD+SUXWz59Dy7DxcTbtQzYWQMZTVNVNQ2cdOIGBbMGIlGHZjVTCfyqnn7o28Ccu0rdLUhkNjzE7J6uxWLS49RdfUWpdphQk0cMr1zlOxadk09ttg+tL9le6QuzoziRkBkAjhtSPGD3CXTrHbQOLr2ut3Becr9uJarwj06KYm3IUEAkZD1OC6Xwi/+eJATee7bgMU0curC1Tkvp87XkJNbxc8fvpWo8BsvbXbKLl5//ySTxsXxndT4TsdmtTl55d0AjBB8y9dfmkhJiicmWYUUJFMfUY1T3QNXnwGlcgQjVBWeryUgtLEZU4gOhd5fe605MhhdVW8ot+oHig3CEsDcNQV8pZRxSAYHEApcvjWqhR4/mb/DZHDmgnZcoAMRhB5BJGQ9zOEzFZ5krC2n82t56PldTEqNJ9Sgo7K2iUmp8QyINvBNQS1fHLtEsF5DTb2VugYbeUX13DourtMbrX7w6XnKqwO/tY+iQH5RA/lF7q8TYqMYPFaLs0lCUoEq0k5tWDWKKvD3egrsBkZ8a3tKtcNMmCUca3AMNlU90PPnw7VFlhqwx49GXx7YUdNuYa9FCtehKHHuchl+ppQVIg0biKLoUU6fQEodjdQn7lfegJwPSoO70KykBykMVKGBjkoQAkIkZD3MP770rhK63eHiy2Olnq+PnK1ss21eUT1bPrvAvXcO63BSZml2sHXPhQ6d29XKqpoo29vy2KQ74qmOC/xWRBeaFWilkLnGbiLEbiJIG05DiBEXPX/laFsaw+04DDcTfOkCapt/V9r2GKog0IS7hwIbTnTNNWzNKKhRSsqg8jw4J4CmF0/m95aryv24QhUN6uTLk/6DAK0om9GdlGaQqwEHoAV1DEgB3FO1HxEJWQ9ysczMkTNtJ1ad8acPT3PgeBkZNyXQbHViarSx9J5xBOu9+xXYe/QSluZeNJLj7BkVw/MazTRHawmWWp8HpHGYiKgDpz6WJoMWJ70zobFp67ENiUGtDEGRZMKKy1A39Z1N4xUpAgqOuwvHItElM+3Lc1GuqXmmfJODlDrK/9fp6Vw17scVqoGg8+92PUIrXPXgzHPP7bv299spgSoONCPc22UJXaZnvGsJ1DfYeOXdnC69xpmCWtZ/eJp3P8nlo32F/O6dG88Hk10KOw5e5KtT5Xy8v7BLY/M31zW5o86pQyMHZnm9w+XiYPPAG7aRAK2tirC6ctT05m2/FGSpARdNmJIG0JhyM9aBqSi9fYaZSgclZ9z/X5lHdy17lFJSu+U6PZ7rEtiPgeMMyJW9c+urnk4uA/t+cJVz/e+34j5u3+9u52erVq1CkqQWj/j4q3Oet2zZwowZM4iJiUGSJM+G39ey2Ww8/vjjxMTEYDQamTt3LiUlJS3arFmzhszMTAwGAxEREdf1cfz4cRYuXEhSUhLBwcGMGTOGV199tUUbq9XKkiVLSEtLQ6PRcM899/jjW+AhRsh6gBN51bzw58PdXkbii2OlTDtdwa3j4q57zmp38uKGbA6dLO/WmPzl1NEGxsSGo64K4djXZnRaFWmZwdTEVHT73LIv6+zcEdz+XRcJFwari4YesId0ZynYsOls2HRgHzEBQ3k5mobA30LuEHUQuLp5pWNwBBj7wOpKf3FdfnOVL4AUBbpMcRvTX1z14DhK+4tHXO52UpbfR8rGjRvH7t27PV9fuym4xWIhKyuLefPm8eijj7Z6/rJly9i+fTubN28mOjqa5cuXM3v2bLKzsz192e125s2bR0ZGBuvXr7+uj+zsbGJjY9m0aRNJSUkcOHCAn/zkJ6jVan76058CIMsywcHBPPHEE3zwwQf+/BYAIiELKEuzg+1fFLB55zls9sB86vvscPF1CdnZglr+8PcT5Pu58n53arbJHN0GUA+4V5x+9VkDWk0Io0eF0ZR2qdtiqbY1ccqRSJqutN222uYKVEGxuAj84gl/cahMmBKDMVjGE1zSRfOvupLDDAPHwaXT3XfN5nqQg0HdD+aQ+UqpBcUEUkSgI+kbnHl4v5LX5W6vu9WvIWg0mhajYtdatGgRAIWFha0+bzKZWL9+PW+//TbTpk0D8CRVu3fvZsaMGQA8//zzAGzYsKHVfh5++OEWXw8dOpSDBw+yZcsWT0JmNBp5/fXXAdi/fz/19fVev0Zv+HTL8vXXX2f8+PGEhYURFhZGRkYGH3/8sed5RVFYtWoViYmJBAcHc/vtt3P6dPt/xH73u98xatQogoODSUpK4qmnnsJq7f6K2B3R6CjlYsNOiho/o9aai6J4v0R94/azbPzH2YAlY+BesdnY5P4k3mxz8l/vneDp337Zq5OxG3E4XZw5a0Ijd+9nkb9VuLAp7V9TAgx2fdcHFADNRhuKStt+wx5IkkwQev1IcldSii926/V6Fbk40BH0DUrz5TljPnBVuM/zo7y8PBITE0lJSWHBggXk5+d7fW52djYOh4Pp06d7jiUmJpKamsqBAwc6FZfJZCIqKqpTffjCp3elQYMGsW7dOoYPHw7Axo0bufvuuzl27Bjjxo3j17/+Nb/97W/ZsGEDI0eOZPXq1dx1113k5uYSGtr6UuZ33nmHn/3sZ/z5z38mMzOTc+fOsWTJEgBeeeWVzr26LuRSZMqaDlBnu1oU02wvoM6Wy0DjFII0kTc42z0/64tj3TdK05aqumYW/uITRg6O4FJlY0Cq73c32aVQszucuPggysusDB+vpzqx/dGrzjA5rHxtHciU4PbfZPWWEhRpEE6NGhRQKWBXW3t9MVkFB87QAWhNgf+995niQIqJQemCchdtqriAkjwYSeodH067lXwR1ENEiYzOkqvxfU6kAq5qUCf5JYRJkybx1ltvMXLkSCoqKli9ejWZmZmcPn2a6Ojods8vLy9Hp9MRGdnyPTcuLo7y8o5PuTl48CB///vf+eijjzrch698GiGbM2cOP/jBDxg5ciQjR45kzZo1hISEcOjQIRRF4Xe/+x2/+MUvuPfee0lNTWXjxo00NTXx7rvvttnnwYMHycrK4kc/+hFDhgxh+vTpLFy4kCNHjnT6xXUV2WXnYsOOFsnYFc1yFRfMH1LcuAebXN9mH6cv1PSY5MfpdHEmv7bHxNMdquusnD5bT029la++MBFpuXEC7Q95zd7/cwtqLCGk/iIhposYzBcx2PrG+pvG+ChsA0b6dI6iCqWhIAJFCvDomuKAiEFgiOie61lqUb45jaL0zRHTzlHAcdxdlFDohA7OU1T8t+J+5syZ3HfffaSlpTFt2jRPArRx48ZO9asoSofLPJ0+fZq7776b5557jrvuuqtTcfiiw3/lZVlm8+bNWCwWMjIyKCgooLy8vMWwoV6v53vf+94Nhw2/+93vkp2dzddffw1Afn4+//znP5k1a9YNr2+z2TCbzS0eXcHpslHedJgLpm3kmbaQZ/qAXNPfsDjbnqCs4MJkv8B504fUWnNbbbPjoLgd0ZOorbouv0aVveN/xLRNFfSFKZ8uLDRGyrg07dc1UlThVH+pIffJ/VRsOIx7nksAJ3I7TEhGB1KkHmKHdc81y75B+XwLillMYL+OUgdK7x41DrwOfsjpwu2ujEYjaWlp5OXledU+Pj4eu91OXV1di+OVlZXExfk+zeDMmTPceeedPProozz77LM+n98ZPidkJ0+eJCQkBL1ez7/927+xdetWxo4d6xka/PY3oL1hwwULFvD//t//47vf/S5arZZhw4Zxxx138LOf/eyGcaxdu5bw8HDPIynJP8On1zLZC8gzvUe19QTNchU2uQ6bXI9L8W4kSUGmtGkfFxt2YrZf9MwvO5FXzWeHS9o5W+hWrq4fgZI78WlewoW2V5fEuJaCadgwHBGDW33WWj8AReXegb36/WxwKThNTRS8cAFF1TOWoErG7v1ZKBe7cUFBb+LqO7XuAkIdg+8fciRQxXRFNIB7sOXs2bMkJCR41X7ixIlotVp27drlOVZWVsapU6fIzMz06dqnT5/mjjvuYPHixaxZs8anc/3B5zR31KhR5OTkUF9fzwcffMDixYvZu/dqmfRvDxG2N2y4Z88e1qxZw3/9138xadIkzp8/z5NPPklCQgK//OUv2zzvmWee4emnn/Z8bTab/ZqUuRQZi6MMWbG137gdDY5iGhzF1FxKpaI8ii2fnfdDhII/nc+2M/zWeGojK3GpumbvQIuzc2UMjA111Idq6M1bLV3hoglbVAza+qLrnms4WkXp0SKiZo65elABe3UDl96qIHh4DFEZIHn5wahLyNVgiISmuvbbdooEyROQBg8D2p9IraBF6uhtqN7IVQMMCXQUvZcU7C766vJhrpUqzq+V+1esWMGcOXMYPHgwlZWVrF69GrPZzOLFiwGora2lqKiI0lL3PN/cXPddp/j4eOLj4wkPD2fp0qUsX76c6OhooqKiWLFihecW6BVFRUWevmRZ9tQzGz58OCEhIZ5kbPr06Tz99NOegSS1Wk1sbKynnzNnzmC326mtraWhocHTz4QJEzr9vfA5IdPpdJ5J/bfccguHDx/m1Vdf5T//8z8B9wS7azPb9oYNf/nLX7Jo0SIeeeQRANLS0rBYLPzkJz/hF7/4BSpV6yMXer0evb7r5laoJDWJxkzCdEMotezH7ur8LVGztYa/bOuddb36upp6KzW7rKSNS+iykhhmh41SOZJEdcfexNXORgzOwTRpev+ogIpgjPk5gHtK8ZWPbC5VBKaDx3BWmin/n/0tT3K6aDxcQOPhAhyVY4i724ikBCj5cNmhO1aMRiSiGpZIe8mYoujArnLPqeoZg4jdw1Xtfs2iJlnHaUaAvRLvSl+o3O39qKSkhIULF1JdXU1sbCyTJ0/m0KFDJCcnA7Bt2zYeeughT/sFCxYAsHLlSlatWgW4FwBqNBrmz59Pc3MzU6dOZcOGDS3qmT333HMt5qWlp6cD8Pnnn3P77bfz3nvvUVVVxTvvvMM777zjaZecnNyi5MYPfvADLl68eF0/ih/mM3b6Po2iKNhsNlJSUoiPj28xbGi329m7d+8Nhw2bmpquS7rUajWKovjlBXZWiDaR4eE/JDYoHamT367omAY/RSV0FYe9a0bHrshu7tziAbWz8yO2PYGLZizD0mkYPhHLsIme4/Y6Hc7K9j/81H96lrz/PE7p+81YLkUTiLllUuyNd2Dwi/pLKCZQlCAUixrFdv2HUFdRDcrBT0ElIQX1jd8P79lB6Zr5w/2GKgK0N9N+OqByt/NzUdjNmzdTWlqK3W7n0qVLfPDBB4wdO9bz/JIlSzz5wLWPK8kYQFBQEL///e+pqamhqamJ7du3X3fHbMOGDa32c/vttwPuHQNae/7b9c8KCwtbbecPPo2Q/fznP2fmzJkkJSXR0NDA5s2b2bNnD5988gmSJLFs2TJeeOEFRowYwYgRI3jhhRcwGAz86Ec/8vTx4IMPMnDgQNauXQu4V27+9re/JT093XPL8pe//CVz585tkd0GkkrSEGe4GZ06hEuWLzvcj15vo399fO19whMlqruw/2xTM3NCOn6+xlqLUR2HrFbjVDlxYsb7oo49iYRNYwZk9I4Iz9Gg8EpS1kynass5XFYHTafbHq10NTswf3kO85fniF14K9GTu/kWpqMKVJqW+3R1ASW75bJ7JXYo0qh0UEsoRQVQkA1jbkPS9tMiskoDEH75/8VoWYeoE9wV+FvbyxKxl2V38Skhq6ioYNGiRZSVlREeHs748eP55JNPPMtC/+///b80Nzfz7//+79TV1TFp0iR27tzZogZZUVFRixGxZ599FkmSePbZZ7l06RKxsbHMmTMnIBPq2hOhG0GdLZcmZ8c2ANfpHdx2SzhfHOmbRVd7u6hwPTVxHdveRytrsKuc7b4XmOydG8FQKQ6CGq8uCJE1oTSGRuKkq+cy+ZfBYkBfnocledx1W1npQyoY+GAkTkcM+b+oRLG1f1uyeksO0ZPHttvOrxQHDBgO5d9073Wr8lGqvlU488IRlIRpSMgoqFHKTEjx0UiS+/dNcQajfL3D3XbYLajiDN0bc1dRp+BZKeg45S4Yq00HdetV34UbUEW4K/ArzZdvBTvdqylVMX6dMya0TVJ6wn1BPzCbzYSHh2MymQgL67oVUPW285RY9rbf8AbOnR3Im5v7262Fnu/mmyMwjfRu/likJRLzmSBsNhf1JjumBjupY8OxppbdcK/MILWGl5L9OwYnq43Uh6mB3rPpsloJIfzcSSQUFFRIrYzyNVXEUPTCp171pwoLZsTq1O6f6K/SojTroNr7yuJdZuztSHFRKKUVkLsfYoYgjR8PTh3Kvg9bjORJd9zXNwrOqoeCZgzIheC8vBJVPQS0aYGMqsvc6H3OarVSUFBASkoKQUHiTkxP4u3PpvcXNupmodrBSKhROvHmN2L0JcYNT+H0eTGnrCdpqHfd8I6HokBY7kAsZhdHC8zXlT85dcbEkIYBxA7SuN/7FJAHNdAQdHWOi9QFc53UsoUQWyKN+gZ6y+1LWWpEDotHYy5rNRkDqPmnezWyKlgLWjUuc+sJRMQdo4n7YWhgJvi7HEih4ShdeZ/bW2f2oJy55uvqQpQjzdBU3/K2qjESpD5SBFrOdz+u5aoNTCyC0EkiIfORWqUjJiiVKuvxDvchSfDDOdVUbQinss6KXqvC5ugdb6R9WV6+mZsjB6K+XCNWUgEqBckgYy5Uo9FI5Jyuv2EfhcWNFF6zzV7wSTXj7oqiLsT9JqH4vE2Jd/RNpajlKMwGBYVe8mbbzrcibPJgmvMrSHh4EqEp9dib47CV2rj0WssRantVIwoJ1Ow3o40MRhcXRHB0VRcG3pLi6sH7c5pb2eopbkSbSXCfoDSA4rr8D1gQeg+RkHXAgOCbsbvMmOwFHe4jPKKB5U804HRoUKtd/O39IRw7K1YLBdrR7Hq/9tdskzmzW2LIbD02jQ2r7MSqaAiS/D8RXGOrJUwJp9kQjUNq6PGJmTMsGk1D23P2DMOCSHluChq9HVygC65AGnR9CR17WT35z32Fs74JgKhZ4wmerqZbRgslDdT1slI2tcUwJLb9dr2WAq5KMY9M6HXER4gOkCQVg4x3EBd8CxIdXwmqUoFO70StcXHfPcUkJ3Ruom366DC+PyWcpL4yYbePaLI6CS68+gZY5+rEMst2aOwmQuuLCDfb0BDRahsJLd1TJkKFclKFckKFvN+JytrydVtCmmgYNhGXpvV6glpdJVptJZKr3nPM1UqO6axp9CRjALUfnUB2tb8pcadJGpS6ZjD3soTMVIESyC2ouoNcJPa5FHodMULWQZIkERt8ExH64RQ3fk6Ts5VbAz7QBzl46MdVfPBhPCfzfJtbFmbU8i/3Sgwd7p5LcfvtKt7ckMSFYkunYhL85/RJM4OHqpFVMvVyEAldXNFFLTcRVteELSQJi7aOa+8PqjFgbLRgD47Aqm5EoWsmd6saDVT8n7c9X4f/+53o5oa3aGPX1GEfmkxQUwjGkqOt9qOownA0BlO5NY/Gr9ufKhA0bABqVTfcslQHg6Vrigh3KUmFOyHvwwmLqwKcJ0GTJspgCL2GGCHrJK3KSHLIXWhVoe03bocxpJkf/6iA74wPb7/xZYYgDf/xUDNDh5d6jqk1LuZ+v+kGZwndzWqTiayIQyNruFRj7JZrSkBQYzEh9jD0SgwaIpDQ4cREszECg/kikXW16JQu2pfumjuGqggj+lnxqBzfGr1VNJj/8ytKFr1D6XtNKKqW3xunHEvu41+S/8xOGr++8RQBbaQRdWgQ1oIqFFU3jBI7G7pvk3F/0gX37TlkV8jF9KaVxz2FoliRXSXIrkJkVwmK0gdW4/YSYoTMD9QqPfGGWylu/KzTfalUcNedlRw/G9zuRH+VSuKRhQpRsfXXPRcXX4NaFY3s6sOfgnuZr/aa0GqC+WSQhmk/ar+9v+gtpVy5Kagg4QgegKS4i4hKKITUF9EYMRi75F4qqCIYCTUyjZ26ruK8+rvnqrdQed/7hN5/K0E/HnD1+GE7thPu/SzN+/KwFtWR/NQE1KoqFElD3V7vly8mZITjxEhTlQM6MZXAF1KwjBIyABo7VpswIKwNKK4gJFUff6NVp7jn+AlecSn1yK4LKFRy7eiprEhIDECtGoZKighYfP2BGCHzk3BdCgmGDDRS5z+ZR0Q2sOxfHdw9LYybx4QRF9163ZIl9weRNKT1W6VqjYtHFuiYfUcYwwZ1z4iM0D6H08WZwkYuVHfRqFQ7JBR0zRVorZUtjoXUX8TgjEZCi4ogwuuqUeP9SG2rIu2EPjD56tdWO87iWjjnXpWoModQs6ZlFXp7UTUFvzqI0zkARQqhZnv7tyhVQVq0MSE4MaKtPUt46CX3G7HUDUmZ3IwULiENnQBBXVf/0N+U4uL2G/V2qsD8G+uNXEo5TtchFL5dpR/ca8MrcLoO4VL8P19y1apVSJLU4hEff3VBxpYtW5gxYwYxMTFIkuTZzPtaNpuNxx9/nJiYGIxGI3PnzqWkpKRFmzVr1pCZmYnBYCAiIuK6Po4fP87ChQtJSkoiODiYMWPG8Oqrr7Zos2fPHu6++24SEhIwGo1MmDChxb6XnSUSMj+KDhrLyIh5xBsmoVOF05mJ0zGxdXx3Sj4LF+Sz4okSVv0fC7d/x/0GqdOqWHJ/MGPG3fiP6vBRl/je7fn84C7/F6HVa1Xc/p1whiV5l+yJaRwtvbErmp40eCkBwQ1FRNbVE1ZXioRMeF0lOqXjk+MVyUHQHSktjjXvPYv5zYOAGldYI6HzJl13nrPOQtFvDlPyxnm8+SbFZA4hcWgt2orj4LAj6YNwHL1E8wc52LNNOApUKOrork3QbGVI8Ymg7sElMK518URfnkHm5jgMzsJAR9HjuZR6nK4c2l+V7MLpysGl1Ps9hnHjxlFWVuZ5nDx50vOcxWIhKyuLdevWtXn+smXL2Lp1K5s3b2bfvn00NjYye/ZsZPnqLWu73c68efN47LHHWu0jOzub2NhYNm3axOnTp/nFL37BM888wx/+8AdPmwMHDjB+/Hg++OADTpw4wcMPP8yDDz7I9u3b/fBdEJX6u1S97TyVzcewu/xTzsLlgm/OJJE0uI7QMN9uJ32xdyjbP/MujgFRQVTWtn07Q62S+PfFagYPKUeWJd56ZwhnLrS+ECFloJE7v+ti+IhSjhwezAc7RDHcK1bcp+POUR0vndIdFKA5LBm72oYL2w1LaUiKFhQVisr9AUByGqh5aDty1fW/d9FrfojqZjVN/12A5cNsn6NSGYJwNdlQh+gZlGGA2vYn1+vnzUYVXOPjtXykTUQpPNa11/CH2KGo0sYEOoqupxkDmuGBjsJvuqJSv0POvjwy5h2JOLTqiV63b8+qVav48MMPWx35ulZhYSEpKSkcO3aMCRMmeI6bTCZiY2N5++23eeCBBwAoLS0lKSmJf/7zn8yYMaNFPxs2bGDZsmXU19e3G9t//Md/cPbsWT77rO3pSLNmzSIuLo4///nPbbbx9mcjRsi6UIR+OCPC70Or8s8tQ5UKxqYW+5yMAWRmFRAd0Xp5gWt99+Zwlj9ewszbWr9dpVJJPPSAnsFD3EPXarXCvB9WMvhbJTtiIvT82491PPboRUaPLUajlZmcWcC/3C1un17x1y/U2BzdM9epoyTAYL5IRF05BrsBFa3//CQ5iKqF/6Dmx/9AqgtxT9Z//mCryRhAzS+2Uv/kPiwfd6zActJkLQkzRzLoJodXyRiAZFChqENw2WKQKw2g8v/2Moqzazca95tBowIdQfdQHKDYQa50F4sVWlAU6+U5Yz6cQ6XfJ/rn5eWRmJhISkoKCxYsID/f+63IsrOzcTgcTJ8+3XMsMTGR1NRUDhw40Km4TCYTUVFRnW7jLTHjsYtJkgqdKgyHK7AlKDQahayJerZ92vrty2C9mtlTDdxy6wVUKoiJvn4bmvAQHQ/OczF4SMt78yGhFv790SYunEuksCiI6EiZtJtK0Omvf3OacPNFZHkIm//RuQnjfcGlqmZWbR3Bv99VQVJkz98cXG+pxKFKxK658rssQaEekp0oaisxz8+m6sm/U/Wv72OcOg7r4Rv/UXWc6+h8FAl0RnSVOT6d5Sq3INfUIx/JBo2GoEV34KoOQR3jn99FRRUEJWf90leXUWngpruQIvW4apqRooORCMCWU91FPu9+AEgGUEWDdkJAQ+pJXEo1vpc/UXAp1ailQX6JYdKkSbz11luMHDmSiooKVq9eTWZmJqdPnyY6uv0pE+Xl5eh0OiIjI1scj4uLo7y843PeDh48yN///nc++uijNtu8//77HD58mP/+7//u8HWuJRKybqDqISt9Bie1XQrjXxcpDEy6evssPLzlrSm9Ts0TP2kgLLz1W45qtcLIMZcY6cVdkIm3FuKUU3j/47ZvX06ZGM73bquk9FIEf/57c/ud9lLHzzfwr+cNjBwcy7r5+QTpeuYIi6IE8/VP9qGOCWHA/DS0eh1NfzuEI6+U6BfuRZUuwSgH4f92B6Y3Pqdx6xG/xxA2fhCRCVZ3Ha3qQp/Pt+/eA1fmlISEIBc7cXy2h6DFM5HkjifEiiYWHCpQyciNWlQDkpCwgmwDh8X9354i7U5UkSr3W7ClHqXmEtLI5EBH1T2UJiAOXHUgXwIpGPdNIhnUg0HSBTjAQOjo3xv//Z2aOXOm5//T0tLIyMhg2LBhbNy4kaeffrrD/SqKgtTBycunT5/m7rvv5rnnnuOuu+5qtc2ePXtYsmQJb775JuPGjetwnNfqGZlCH6eWggMdAgDxCTXcPCYJQ7DE0CEOamo17PmqidtuMTIw6UKLtoOHlDP9u8PYuc8EgDFY02Yy1hGTJhcQHZXIyTPBqFQwbpQVjVZmz/5gyqvtzJ3rjic8ooE7Jg3j869Mfrt2T3SuyMKZijhuTup5hUYdTWGcfv5rGk67tzmq35vH4LtuQq0YQIGaZ7YQNHEoYU9m4mroXIHka8V+bzgNF2oJTgyn7usCIpKA8qKOd3jNBF/q63Hs/hwAxabpcHUERROL/MWXLY65qktbNtJowRiOFGSEIAOqkCBoLOzYBTvr9B5c+hCw1II+BGnS94G++4HnOnIJyK3N21RAM6Lbwwm8jqYAXZc6GI1G0tLSyMvL86p9fHw8drudurq6FqNklZWVZGZm+nz9M2fOcOedd/Loo4/y7LPPttpm7969zJkzh9/+9rc8+OCDPl+jLSIh6waDQqZgM9XRLHffhset0Qc5WLig5W2kjAwtWt31w7qSBFOnXqCufiiHT5nRqPy/THL4yFKGj2x5bHEKlJe2XK4+bepFYqKSUKkU7HYVO/c1YWnumSNJnRHfgbmB3cFpUaj+8nyLY0W73HO/UjKScVksWLPzsT7o/bwPb8WlacGUT+jMRKTWNsrurNhYJK3S4q6Nog7DVQ1yeTU4ZbQTYpDkVqYcqIKQT5xp/xpOB5iqUUzummoyIA0Zi4pKULq5cKnTDk73RvfYGsEh97N3gVZuz0oR7ppl/ZBKikFWfN21QUIldV1JEZvNxtmzZ5kyZYpX7SdOnIhWq2XXrl3Mnz8fgLKyMk6dOsWvf/1rn659+vRp7rzzThYvXsyaNWtabbNnzx5mz57Niy++yE9+8hOf+m9Pv/qnGEgGbVzAE7LW6IPanj+iUsE9c4sYljyIqKju2ahakiBhYMtioDq9k+9MvvqpdlxqKK/9TwhmS9+a+xKs7Xmvx2ENI++1tldBFhy8CCoVScOCUez+jV9xAZXun7tUeeHGjTuq3oT1HwfQjBmFOiEKVXANLpMa+/Z/AqC98zbaWvvkshqhvmOrNpXCM7iGjEHVat2n7qNUlSEN7oZ9P3syzch+W0BWkoKQGODjKssBSJL/FsSsWLGCOXPmMHjwYCorK1m9ejVms5nFixcDUFtbS1FREaWl7pHn3NxcwD0yFh8fT3h4OEuXLmX58uVER0cTFRXFihUrSEtLY9q0aZ7rFBUVefqSZdmzqnP48OGEhIRw+vRp7rjjDqZPn87TTz/tmX+mVquJjXXvRbxnzx5mzZrFk08+yX333edpo9Pp/DKxX6yy7CZ22T+lL7qbTu9k4ncKSRle2n7jbhIe0UDWxJ5xG9ifzpbHtt+om33z0nEqP829cSOXC83gwZ4v1RHhaEaPQRXWue3EpO746+SwQ00Nzn0HsL33DxznZJzHrk7MVw+KQJJbuVUvaXGdzunUpZXCs8h1oOgHg3Fgp/rqsNCIwFxX6DHUqmF4nwqoLrf3n5KSEhYuXMioUaO499570el0HDp0iORk99zGbdu2kZ6ezqxZswBYsGAB6enpvPHGG54+XnnlFe655x7mz59PVlYWBoOB7du3o1ZfXcX+3HPPkZ6ezsqVK2lsbCQ9PZ309HSOHHHPd33vvfeoqqrinXfeISEhwfO49dZbPX1s2LCBpqYm1q5d26LNvffe65fvhahD1k1M9gK/bK0kuJWWDGDj3zTMna4mIcHMnzaFUFXXgyZPd8Crj9gZMaBnjKIq6Dj6RDZ1Ry561X7wXTfhOudOZLSjR1Ow4wQAKXeMQq6sxNXo+yrj2NtHYGjoWFkMv9FoCPrxTCTXt7Zw0oTh/OJrv15KGpaGSi7rvtuYGj3SlFlIUu/+d9NpmjTQDAl0FF7pijpkcKVSfw43Lg6rQqOagEqKv0EboTWiDlkPE6YdQrBmQPsNBa8kDqrkmeWljEsrJirGxE8ebCDU0EuqpLeh0dZzVnm5HHqvkzGA0kO5aAcmAiAXFxE0IAKAqvw6Sgub0A72fYm8+WwlZs04GoPTaAq9CWf8eJ/76LS26oo5zRDs3w3MlQsnkU1qFF0SSkiKe9RMF9plOwxIE78vkjEBAJUUj0Y1GYk4rt9hRkIiDo1qskjGulj/vHEeAJIkMSRkOhcbd9Pk9P9+YP1dRJSZf39YzZ82Gaip751vMucrjaQnBToKt4t/L2m/0TWcDVaKT5YzKHMMNecrcTa7y0g0XnQXnWyW9T7/sbFVmLBVXF1dK+nUDJ4yAOq7dyNvucyCJk5Fi9EDtRGa2y4j02F1FbjqWpnPo1JDaCTq+Aiw+mG3AWMUBGtQAMmPJQyE3kslRaBST0RRrJfrkzkBDSopxq9zxoS2iRGybqRW6UkJnXl5n0vB32Ji63j80TpuGdfzbll74x9fO6kwd27elT80FIWQ/8cv22/4Lc4GK4U7jtNwoQxnw+VK3pLEwNvTCA7p/Ge/oMTIbk/GABw7PsNxruWCBaW7S9m4ZDBVgybEP/1ZalH2fICy5x8oDf38bcB5Eqw7wPoJOHp4Yd9uIElBqFWDUKuGoFYNEslYN+rn/xK7nySpUPfLAoTdwxjSxAPz85k5pfclvVV1NtZ/4Z/q1x1Ve0LH4SXv+62/sOEJ6FQOlMsFGiV9+9t3tcVZ3wz6rkmEpJgBENRK3yGhqMffjBTRMlF2VQaqRImfy8+4ZJRjO1Do2Vt4dT074AD5onu7JUEIAHHLMgB06tAeWQKjL8nIvET2qRgq6/y751pX23fCTPXtRmJCun+rrYaLRo7+29/82qc5rxRznnuFbmRqMvXnLhE5ejDhMTocF1qvW6YdPRoAR24uXLPmaEBWIpT7f5K/9tbvgPkiRBkhYgxyjQXJaEAVJEFtAWhtSE4LqENBdidiiikwW125mu0tPkW71IkgO1GFBEOj93P+3CRIGAXRA7nxZO7+xAH2/aD7br8thSEEjhgh62bNzhpMdv8X0BRaCjZYeWRRA8H63vfJ/91Dg9tv5GcOaxinV+3p0mvUnbqIYndSeyKfqgu11z2vjorAOXAYpdmFFOw4gVkbjWb0GLi8dL3qcAVE+2GSnSS5i+yFhLqTsbo8kO3u24K1BailSlRNhe5kDMBUilKYi/PLIyiuAbgaw6DM1+THP5T807jkGBRDCi7NIJT80ygXc5FPHwe9j6PCQ29BNWYYqgFBSAGshdbjKA3gEh+Yhe4nErJuZpf79hZAPUlktIkHZnf8FlmgZOd1/6IEbZCZSX/JIHXtDwhPH4Qu2til12u8WIk6smUC0aSJoPzAWWzV7pp95rxSCnccp1Efg3bEcNTBOjB1sFp/sAH12DQA1GNS0Y6KRzsszp2M+UA+9AWuE/4td+ErpSQP19mjKBdOXnsUV4OEYkyB4GuqqGtuMD3C2Ptu63cbxX/bxAmCt8SYbDezytePDAhdR63ufZ/8V80PTNIu4ST+eyrivzcBF2oshUF89SP/3sK8lskeTHi0GrnG/W+i/lzr+3jWny2m/iwk3Z0OSscKFGtTU6EuD9V3bobmOmhuBkff2sNRKStAKSsArR71TelQlYs0aTZoVShmC5z41L110hXq3jd63G2c+e7tlKTeXUpH6F3ECFk3anSUUmU9Eegw+pXSst63gCJI07VlCBRVy++JHDkWZ+xYHLGjccaOQ44ciyt2NMG3JDPlxHJ08a2vWtVHGYm7dUiH46g/U0RZQSPa0aNRjxqDw3T9vLmgQXE0BccQPH4sB187xLnyob5fyBgKjZfLeNQWQHN9h2PuFRw2iBmM9L37Ub76B6CgilAhTZkNyelX2536XNyobJMDnF20XVcPJysWrM7zNDvPYnWeR1a6fz5rfyVGyLqJ09VMceOnBHLfuv7I2j1bcPrV7jPxzL7JQaTB/3WuFH00LkM86rrTVw9KKhTp8mR1QLkyKCCBygBxsyYQMXkIjtomLr3zFS6HE1dtE8NuT0Qqv0D4valUnKhk4M0xVF2wEBSup6HEjNPqIGJoNJXHL2Gva/2Pur2u0VPVv9XndaHUfnOa2m8uodGrGZl0CXxcp6FKGAiqnrlxe5eIjkeKNyJJzSiRA1HMTRChRZJsSMMSUVKGopibkIxGJPrWKKFfuaqA0YGOots4XNU0O09idxXT4n3KKaFTJRGsSUOr6rpNxQUxQtZtnIoVWemF2UEvp9P2vgT4r583svL9QThlP5c4AOSQhBZb8yiA0s5t3aHPjCfqjjDi7k0g/W/zSH91DiPSZKSiM2C3UXG8guTRCuri0yQOtBEhFzJ4hJOEmxOItOUy5PYUAJKmjiJxynCv4jSMSMYZO4jiL7/xHEubNxKsvn9aV4WGgK3/fMpX35yFJLlLN0hpNyEZDVy7ilJSWd0jZlqRjN2Q0gWFf3som3wRk/1j7K4irh80ULC7ijDZP8YmF/n92qtWrUKSpBaP+PirOwJs2bKFGTNmEBMTgyRJnk3BW8Rvs/H4448TExOD0Whk7ty5lJS0LG69Zs0aMjMzMRgMREREXNfH8ePHWbhwIUlJSQQHBzNmzBheffXVNuM+f/48oaGhrfbVUSIh6yZme2GgQ+iXeus0mfMlFv55yr+b+CqoUNTWFqUkXOEjUSQvkxVJQdLaUcWHoFiuTnoePKASpcZdsNVVVQZ2G4qpjmDTeQCC1E2MfWAsEc58YuKcaMOuFprURRoJGxaLNjSIkORoADThIdSUNVF+5AKK82ryGJOkc6+Q9PV1y/2rpIMUF+n5f6XOCVqHWEXZIXZQ+v7vjsNVTYPjC9ovfeKiwbEXx7f3dfWDcePGUVZW5nmcPHl1wYrFYiErK4t169a1ef6yZcvYunUrmzdvZt++fTQ2NjJ79mxk+erfD7vdzrx583jsscda7SM7O5vY2Fg2bdrE6dOn+cUvfsEzzzzDH/7wh+vaOhwOFi5cyJQpUzrxqq8nbll2E5WYHBoQml78G55TqGXuTf7pS9FGIkckAhYUnQ5ndCqS04HUgY2smzZ90X4j2Ykiu+fCKZcueMqOKpcKGJ0qIen0IEkoNgsojTAAkKxUDhhCTYOemlZuY+5ae5xBkwdy6+xQdDXer46UT+agumkENHZ/lf9uN2Q0aN33dF3FTci7t6D5l0dA100blvcpl8crnEXgPAs4QT0UtGMCGpW/NTtP4n0dOhfNzpNodXf4NQaNRtNiVOxaixYtAqCwsLDV500mE+vXr+ftt99m2rRpAGzatImkpCR2797NjBkzAHj++ecB2LBhQ6v9PPzwwy2+Hjp0KAcPHmTLli389Kc/bfHcs88+y+jRo5k6dSoHDhzw6jV6Q4yQdZMw7ZBAh9AvDRvae+cOHTptZufZDkxi/xaXcQjOyEjPSJgiNaGoG3HpbchBvi8gCJpxC2g7kekqCorNimJtbjFah6IwQFPA2MRifvAfSUx/OpWpT91E8pQhniYlhy6x9dlvOHomGWdUinfX02lB3Yszc1+o1UiAggb50w8BUBq7pziyggpF6aVD0q1ygfMbcObiruTvAvkSKH1n709ZsVyeM+Y9u6vY7xP98/LySExMJCUlhQULFpCf732tzuzsbBwOB9OnT/ccS0xMJDU1tdPJkslkIioqqsWxzz77jPfee48//vGPneq7NSIh6yYaVTfvfScAkDioku+k9c69LQHe/gxkV+fmkrmCQvBnJXb1YB10Yguk9ijNFpSaCtSl59CVnWXsoDKmP51KePL/b+/M45uq0sb/vVmbNG26r7SlFChQClZAaBFEWSoIwoAL6Iu4DDoOLowwizoj6KDg8qrz/mbUGYYRXJAZERUGBEEtiiwCUmWTtaWUbnTfkzS5vz8qgUCXtE2bpJzv55MP5N5zz3lObu+9z33Os1xcijux5TQf/ekkxwr6IBvDW+7QZMKy/zAYoztNZo+h8OfUIRbVxeW2qs5/Kamu8ePZp+spLHJRrU1PwXoKxyiSOrB0n0h5izWftgeayVhs+S6TYfjw4bzzzjts2bKF5cuXU1BQQFpaGiUlJU4dX1BQgEajITAw0GF7eHg4BQUF7ZZr165d/Oc//+Ghhx6ybyspKeHee+9l5cqV+Pu7/rkiFLIuoqbBdX/AgrahVrneOb6rKKkwsfdM2+tbyoD8c91DSXax/5BkwzB7smv7bAlZRpl3nNTpVypemR/8xNrnCzhrGoAtIKrlfpT6ThLQc1AOuwEAOffi8uyFpWNXIKOw/11dyj/frCTrVC2fb6rp/t5qtnPdxrdMpn11O2UX1vucOHEiM2bMIDk5mXHjxrFx40YAVq1a1aF+ZVlGaofPKcDhw4eZOnUqzzzzDOPHj7dvnzt3LnfddRejR4/ukGzNIRSyLqLBdvVE7Hgag5Nr2+ML7jHsPtF2q4MtcAANof2QVf6NJYFcjKTs+luHlH/awUp2AZvFxs43DpJbENByB7buH1Vo/epTLO/+G2vG+osbG1ynkJ0/78eiP9STlW1Eli8uA5eXNT6gv9hSTEGBERkFhw/7c/JUd6wGoMHlRd7dhET7fJulTvSJ9vX1JTk5mRMnnPMTjYiIwGw2U1bmWF+2qKiI8PBWrOdNcOTIEW666Sbmzp3LH//4R4d9X375Ja+88goqlQqVSsUDDzxARUUFKpWKf/3rX20e63KEQtZFWG1dXw5H0Eh8Qj4jBnvvg2H/CRP15rb5QEmWOpDqaAiMRla53q9HfV0YyoSur7kZndK04y+AWtvCQ1Ktvjqc+gEaHK0XUnCwy7oOC62gotzC4j+c4XfzKzl82J/iYiNZpy6+cL66NJ8//6mel/6cw5+fPkNZufe6DFyBFACaEe2K9vVE1MpI2q5cSqgVkZ0hDtCYwuLo0aNERjo3xpAhQ1Cr1WzdutW+LT8/n0OHDpGWltamsQ8fPsyNN97InDlzeP7556/Yv2vXLjIzM+2f5557Dj8/PzIzM/nFL37RprGa4irxdHU/SoX31VTsToy7qYhdmd55DkoqTCzd2JuFE7Mw6AGbFYmWrR5S9RnQx4NUh9wZzw7Jhv/jMyh77LVO6PxKasOSyPz4NBVnjza5v+/EXoSEmOBStxONFsnfiFxcBDpfUGkdSwddBSiGjkEKVtCRhNQyYDb7UlSk4uwZK+Xl5QAUFZp56c9X5qUqKjRTVHjxd172bCFLX/VHIblumcstSIGgGdltlDEApeSLRhHzc/4x59AoYlBKrqt1u3DhQqZMmUJsbCxFRUUsWbKEyspK5syZA0BpaSk5OTnk5TWWTTt27BjQaBmLiIjAaDTywAMPsGDBAoKDgwkKCmLhwoX2JdAL5OTk2PuyWq32fGa9e/fGYDDYlbEJEybwxBNP2P3PlEoloaGhAPTv7xhhu2/fPhQKBQMHDnTJbyEUsi7AKpspqN3rbjGuaixm747+2nu0ilcV8Tz1SwuS7IOy+ChSC476EjaQtSB10lK5TU3Nmq86p+8mqDhvoeJs8zU+c3adY/CIsMYvPr4owsNRRgRDTSHEp2DJPAyqcODqKhqt6Ncbqa2lDS5BRsH/vWrl+++arjPqDAX5JpY+W8tvnzaiVtdSV2dAr/PC6GeFX7dSxi6gUyVjNufiXOCPEp0q2aXj5+bmMmvWLIqLiwkNDWXEiBHs3r2buLg4ANavX899991nbz9z5kwAFi1axOLFiwF47bXXUKlU3HHHHdTV1TF27FhWrlyJ8pJElM8884yDX1pKSmMZsa+++ooxY8bw4Ycfcv78ed5//33ef/99e7u4uLhmU264GkmWXe3x6x4qKysxGo1UVFR0SvRDRzhf9yOFdUIhcyclxQEs+3/e//7x19+HEhNZjiTrUdSbwVKFJMvIkhLJXIZkq0fWhmL1C0NW1NJppbosWkrvf6Vz+m6C89p+7FvVcnSbT4AWH6MP1QXVjP7jMKKCTl7cqQ+E2rLmD+6OKJSoZt+LpGi/u4QsK3nqt9Xk5Xbc5SIm1oe4eD07tpfy+t9jKSqAHw7UM3GyFj+DFyjKqsGg6vpl+ktp6TlXX19PVlYW8fHx+Pj4NNND05isOVRZttOyUqbAT30DWqV7fwNvxNlz0yYfsjfffJNBgwbh7++Pv78/qampfPbZZ/b9siyzePFioqKi0Ol0jBkzhsOHD7fQYyPl5eXMmzePyMhIfHx86N+/P5s2bWqLaB6LxVZDcf0P7hbjqken6x4+fK+vrgQac4lZdQ1Y/XU0GPVY/bU0hETSEJpEg9GIrKihU+umdnGQWYATblD15SbKz1TQYLKy46XvMesueXBcJcqYInkESArw0aO66752K2M2m5Z/r1az4xsfqqtdExRyNqeeHdtLAXjqN7m8sCiHjZ8U8fv5eXy0Vku9ybfJCE6PQDK6XRnrTLTKWIyaiWgUsVzpUyahUTTuF8pY59Imk0GPHj1YtmwZvXs31qNbtWoVU6dO5cCBAyQlJfHSSy/x6quvsnLlSvr27cuSJUsYP348x44dw8/Pr8k+zWYz48ePJywsjLVr19KjRw/Onj3bbHtvoq6hmJzqL0UNSw9Ap69DpTTQYPVug3BNXUuakOx8GaSOomnA56YRmPYdRq7sfOuGpiIXpVaF1eRcxKC5ykzm+mqGTdQiNXQPZbxVDAEoh/ZGkTIQFFYkqf1Llbt2qti0vv3LlK1RW3vx77im2sr6tYWsXwsr3ouktEzDn/90jlf/GkpJiYaI8OaXqrsGFahdu0zniagVIag1N2KVa7DY8pFlC5KkRq2IdKnPmKB52qSQTZkyxeH7888/z5tvvsnu3bsZMGAAr7/+Ok8//TTTp08HGhW28PBwVq9e7ZBc7VL+9a9/UVpays6dO1GrG0NpL6wdezMWWy35tbuwXaaM+aoikbFR21DoJsmuTmQZlEoFDVbvLiFTWW3FZtOj6MAylEuQrOjvG4Z+9kjKHv9Hpytlcn19m3MKHf/kOOWnw0gYH0dCrzOdJJkHYWiMJJaUHcvMf/SoP//4q+uLSDvD66/UcDCzMWfjwkfOU1Vt5brUAB58WI1C4aYXW1VvUFyZbqW7opR8USp7u1uMq5J2p72wWq2sWbOGmpoaUlNTycrKoqCgwKF8gVar5YYbbmixfMH69etJTU1l3rx5hIeHM3DgQF544QWHoqBNYTKZqKysdPh4EmqFnl7+U+gf+D8kBswk1jCevsY7ifefhFrR/RNUehqV5f6YzN6tjAHU1NtY8bEHBSgoG0DRyctM4TEcy4ugob7tUXpFPxZ1l5RRLaPSoBp9U7sPN5l9kYGaWj9efM49yhjAwcyL9/Hy8gasDTK7vilj6XM1nM01UlXdxSsnyr6g6tO1YwquWtrs5Xzw4EFSU1Opr6/HYDDw8ccfM2DAALvSdXkitvDwcM6caf7t9PTp03z55ZfcfffdbNq0iRMnTjBv3jwaGhp45plnmj1u6dKl9mKhno5a4Yta02jytckNVJiz3SvQVYgxsJInHgzh1X+4W5KO899vKrhvqj8qlQckOpUVyBWd+zLUoPTl9FftL1cTm2SDbpqXudR/ED+cDyeifw96mPX4aSyo1S1P9kIaC6XShkrZ+Df0308bOHtGprysBE8M8zr+Uw1/XNi4HD/7gSiGDVdh9O+Cl3BVx2vJCgTO0maFLDExkczMTMrLy/noo4+YM2cO27dvt++/fFmhtfIFNpuNsLAw/vGPf6BUKhkyZAh5eXm8/PLLLSpkTz75JE888YT9e2VlJTExMW2dTpcjoUCBCls7S1YI2ockQXGxnu7yZN5/VMvwZDcrZA2aLrE+qcvOolApsDW0L5Lg86U53LLAB5vaF5vkg6o2z8USuocdDeNY+eHPEVsZ5wHQ6xW89H/R6HQN7NmlJKGP0u6DJQOVlf786+8VZO4/hyTB4GuNlJw3UVhQgdnsgZpYE7y7Io/wiFiSO92tSwWdmJFeILicNitkGo3G7tQ/dOhQ9u7dy1/+8hd+//vfA42FPi/NsNta+YLIyEjUarVDvpD+/ftTUFCA2WxGo9E0eZxWq0XbiQWOOwtJUhCo7UOJ6Yi7Rbmq+OrLXmz+2rOWtTvCCyvO89c/hBITUe4eAWSJssffIuDFXzUWGq9v2adN1asPXOqGcMVLmuTwz6Vffvregq2h/VGSZcdL2PVJL3wClMQN1xPUTZ6x72dcef+rrbXxyC/P2r/7GpSkjQ5EQuLYkWrOZF9cjpRlyNzvbof5ttO3ny8DB3bBi5WqCT8qWzUofi5lJjeA5P2pdASeQ4f/mmRZxmQyER8fT0REBFu3brUnXDObzWzfvp0XX3yx2eNHjhzJ6tWrsdlsKBSNLm3Hjx8nMjKyWWXM2wnXX4eMjXLTSfw18ehV4eTX7kTu6lwCVwkNFiVbv63G5h0GAKdZ+Goxq5f5onSHg78kE/DirzDvPuWgjOkm34jPzSmglLD8mEv1m/9GERaM/s4bMe87TP3OA1DThoepUknOzo5fF6c+Ow0SpIyO7PKUHZ2BxRCNxQmXyJpqK1s3FXe+QF3I3F+HIEldoEjKl1xXF5SvhiOAGlQJYN4F6sEg+TYmjRUIOkibnPqfeuopvvnmG7Kzszl48CBPP/00GRkZ3H333UiSxPz583nhhRf4+OOPOXToEPfeey96vZ677rrL3sc999zDk08+af/+8MMPU1JSwuOPP87x48fZuHEjL7zwAvPmzXPdLD0MhaQkynck/QPvoYdhNEE+iWiUnpXMtjtxLjcUSzuXuzyZerPM57vcZyWWDGa0N130sVGEBKG7LQXJaEEymNGkRqLq0xPdzdejGqBFf8+1GBfc/fPBTg5itXLDXNdEfF3/5DCwua7QtjvZX5nI1RGtcJGUoUaefTGO0LAusnRbcxsVMVspmLaBaTvYCsGWC+ZvADNY9oL1bKtdeRMWWw1lpuOU1B+mzHQci62LUukI2mYhKywsZPbs2eTn52M0Ghk0aBCbN29m/PjxAPzud7+jrq6OX//615SVlTF8+HA+//xzh5xiOTk5dksYQExMDJ9//jm/+c1vGDRoENHR0Tz++OP2JdDuzKW+dRIeFDnXzcjP19FdS+b8fW0JNw4NwEfrppumwoLP2FSseUX4/WEqKC7xjZSs+P9p2s9fGs05yl7+BLw2H4VBRfWKbZh3Z7bYvRyZwOevd3x5/9qHBtEzJpfuYibthhV8WuX2uwKIjurKJVYrmD7nwt8u8qV+v5e84MkdSzPiKdQ1nOd83Q9UWnJwTCot4a+OJVQ3GJ0q1F3iXRW0yUK2YsUKsrOzMZlMFBUVsW3bNrsyBo0KxuLFi8nPz6e+vp7t27dfUXQzIyODlStXOmxLTU1l9+7d1NfXc+rUKZ566ikHn7KrAaNGRPN0FudL2p3dxeORZXjzQ/dafXymDEd/1wRHZewCkrXxcwGlGUWIFXxMqBNaCcLRaNmx+qyjEiVB0u/GEj1xQJtkPLM9jyOZ3edhEuBz9SWb1um6Wpm2YVfGWqIbKGSV5mxOV26k0nKGKyt8yFRazjTu74QMAYsXL0aSJIdPRESEff+6detIT08nJCQESZLsRcEvxWQy8eijjxISEoKvry+33norubm5Dm2ef/550tLS0Ov1BAQEXNHHDz/8wKxZs4iJiUGn09G/f3/+8pe/XNHuP//5D9dccw16vZ64uDhefvnlDv8GFxAeiR5CiM9ATNYyys0nW28saBNR4d6ff6wlMvZV85u7NSC5x/qjCLZCcNtvJdqxidRu3I5c3swSlNlE2t19ISgA37tS0QSoUOpkJJUF2TaMgq1pfDnln01WiFJoVdguyepf8lMxSh8VAwa1WUyPJManEAhwtxhdir+/hyqhXh6JWddwnrPVGcitKJ8yVs5WZ9DL/xaXW8qSkpLYtm2b/fulBpmamhpGjhzJ7bffzty5c5s8fv78+WzYsIE1a9YQHBzMggULmDx5Mvv377f3ZTabuf3220lNTWXFihVX9LF//35CQ0N57733iImJYefOnTz44IMolUoeeeQRAD777DPuvvtu/t//+39MmDCBo0eP8stf/hKdTmdv0xGEQuYhSJKCaN/R+KiCqbacQ6Pwp67hPHXW8+4Wzevpn1SI/gsjtfXdw3+oKWQkpM6sXdkJyCa5eWXsZ5R5x9GPnoRPjA24+ECWFBYi042Ejojn/K4sAHwi/UlacCM97+yHT7jM1nEfU7I3G2udhcC+wQy9tyfQPV549BUnmDoigU93Xx23cL1egbKDFQg6DbnSqyMuz9f90KoydgEZK+frfiTWb6xLZVCpVA5WsUuZPXs2ANnZ2U3ur6ioYMWKFbz77ruMGzcOwK5Ubdu2jfT0dAB73tLLV+gucP/99zt879WrF7t27WLdunV2Zevdd99l2rRp/OpXv7K3+f3vf8+LL77IvHnz2lxN5HK671qOFyJJEiE+A+npl06UbyoJxlsxahLcLZbXo/et45YbdW4Z20/f+PZsNKh5eLaGfvEGl4/h66NAkrwvaKHhpHMvG5qUpq8BWVYSMqyxzJrKz4fp2b+m3+O98YloAMnK6H/P4PbChdy+Yza3PC4RpO4eytgFtCrvUsA7gsFP5bkhDHItmL4Cyw94ZFbdFrDYan72GXOeSssZlzv6nzhxgqioKOLj45k5cyanT592+tj9+/djsVgcqgRFRUUxcODAFqsEOUNFRQVBQUH27yaTCR8fH4c2Op2O3NzcFhPgO4tQyDwcgzrK3SJ0C5KSCju9ws/l3D7Rj6cXFjBnhp6H7jHRq3ced04/T88o1xbqHdDLp/VGHog1uwDUrVsVyhf9A7n2yhQ4h5ce4uj/ZQBwzbMTkS7zYdOGWFDqzGgDu58/arUxkf/s8O6lsrZQVGimusaTU0vUgzUHsDU6/1uLvUI5q7aco8k1/xaRqba4Lrny8OHDeeedd9iyZQvLly+noKCAtLQ0SkpKnDq+oKAAjUZDYKBjvdHw8HAKCgraLdeuXbv4z3/+41CHOz09nXXr1vHFF19gs9k4fvw4r7/+OgD5+fntHusCQiHzcNQK11tU2ktZtT/Lv0zig51JVNR4jlzO4KOrx6DvmgeYJIFapSA+vgKlUmbgoBxCw0sBMPjXcM+sEvx8XSfL5NGuVfC6Cp9piSgjw1pvWG9CLr/Mf0iW+PG5zfavx974horDTS+7yD+1v+ySp3KqOrL1Rt2MFxafp7LKk9MDqQErmHeCZRfYPL8ihE1uX8UYm+w6f76JEycyY8YMkpOTGTduHBs3bgRg1apVHeq3tSpBLXH48GGmTp3KM8884xC4OHfuXB555BEmT56MRqNhxIgRzJw5E8AlgYhCIfNw9KowVJL7i5FbGhT85fNovj1dy5YjtfztixgsDd7jM7FtWzyVNZ1Xrio82If064346dUs/JXM838ssithl+PnX81Dsy3otB2/gLVqieQ+Hupb0xpWDdazzj20LMfPOW6QZAb9KR1jUiQDnxxPn7lpGBKaXpaW+nUTT/5LqDJ5z7XnKs6drefRuTn8659KSsuMyLKnWT4tYNrS6FMGYHPOwuNOFO0MSFBInZe03dfXl+TkZE6cOOFU+4iICMxmM2VljtU8WqsS1BxHjhzhpptuYu7cufzxj3902CdJEi+++CLV1dWcOXOGgoICrrvuOgB69uzZ5rEuRyhkHo5CUv3sQNk16231Zg21piuTje4+0Zvs0osP/uNF9azYnkhN/cWH4OmCaDYe6E+tqXGbp6R8Onc2jG27nM9fNDTJn9sn+vHQ3RrCg1tfDgwP9uGRuUWMG3+K3z5aRlhESat5osIji5n/YD0JMR2zbt0/LchznZ1bQa7F6dWSmpWfgux4uxr49AAmZ97F4OcG0f+JPiibSQUh9w2G6fcgq7rPEp+5wWM9qjqd7dtK+M3DZ5g3t5yjR/2xyd2zoktXYFBH0/Zni9SprjQmk4mjR486lGBsiSFDhqBWq9m6dat9W35+PocOHSItLa1NYx8+fJgbb7yROXPm8PzzzzfbTqlUEh0djUaj4YMPPiA1NZWwMCes/a1w9b1meSF6VRg6VSh1DUWd0n9NvY4vDsWz94yNs2WN5UIC9WpSYtTEh1gorFSx6dCVhax3Z9XyQ24UKTE+KBXwzclaoJ51ByLRqRsfnv8zXGJEX+fedDoLrY8FnEy8m5Tgx513XHQojTuYQGFJ8wqPTqtk1i/M+OgalQGd3nnlKCikgl/eW8m3O+LZmFHZLpeTEKP3vlNJBitSkD9yaSuZ1331+P3qNtru63IROUSC+/4H2aZG2rUfjuxvd1+eQIPt6lXILlBTbWXZs40O6UNHBDDtNiM9elR4jvO/5J5AoragVvjir479Of+Yc/ir41ArXOcmsXDhQqZMmUJsbCxFRUUsWbKEyspK5syZA0BpaSk5OTnk5TVa048dOwY0WsYiIiIwGo088MADLFiwgODgYIKCgli4cKF9CfQCOTk59r6sVqs9n1nv3r0xGAx2ZWzChAk88cQTdv8zpVJJaGhjmo/i4mLWrl3LmDFjqK+v5+233+bDDz9k+/btLvkthELmBdQ1FHeaMgawMbMXmw451hcsq7Xw5TELHANofqmvzmJj52nHY602mWpToz/PW1/D+aoBTLzmJ1RK90QChoSWMTSpF/sOVxIf7Uugv5LDJ6sxWRzlCfTXMGOaY+SfsRk/Yr2Pil/crKV3QjEG//ZHHKlUMjeMOU19fUKbrHgXCApo99DuR7ISsHQuZY//FVQqAp77JVWvfWhfxpT8/fD9n1vQDI/6OelsB02ukg2UJuTrhiB5uUJmsXqM2uER7Ntdzr7d5Sx5JY6YHh5SMF0Z724JnCJUN5gqS65TqS8klITqXOsCkJuby6xZsyguLiY0NJQRI0awe/du4uIaI6jXr1/PfffdZ29/wWdr0aJFLF68GIDXXnsNlUrFHXfcQV1dHWPHjmXlypUOfl3PPPOMg1/ahZrbX331FWPGjOHDDz/k/PnzvP/++7z//vv2dnFxcQ4pN1atWsXChQuRZZnU1FQyMjLsy5YdRZJlLwgFcYLKykqMRiMVFRX4+3uy42fbOVv9FRVm58OA28qOn/ryzx2d518FEOGv4VdjKukZ1vFIlPZgNispLQ4kPLIYSQJTvZrcs6H2fYVFavr2qSKqh6NC9tFHCez+8cob/NRx/lw/ynXnJPdMOH/5V9sT2M67I5gJaV1U26+TkEtVWI6cQ3N9OMgKrGfMmL/7CZ9J1yIZOicZqFQC8g/fI5082Cn9dyaVxgE88Z94rrZals4wYVIod9/Tufcyp1CEgCbV5d229Jyrr68nKyuL+Pj4K1IztNqvObvV5LASSmIMY/DX9GyP6Fc1zp4b713vuIqob3B0Dq2sNZBfFkJheRAmc8f9YkYmHucX13Sueb2g0syf/6vjVEF0p47THBqNlYioYrtvl9bHQkKfPBL65NE/6Sxjbjx9hTIGYPQHrcZxudOgVzF0WO4VbTtCVEwhCT3avgywZVe1S+VwB1JQA5q0n60Jkg1lTxW6OwZ2mjIGIAcDo1O9LJVuIwZTHil9vFHyzufokWoPOKcSqJLcLUSb8Nf0pJf/Lfire3Kloi/hr/55v1DGOhWxZOkF2H4uZHu+IpA1e6LYn3NxiVClCOCxsTKD4rLa3b8kwZQhR9h6tLd9qbEzsNpkXtuq49djYunfI8crCiRfd10hB44EUFR68XeZfrMGHxfXElQo4JYJ9fzfv9p2XE6BhUPn/RkY6qbi4i7BAAo3KJYqE0TFQ177rx13oKgvZ16vTRRfcw1fZ0fw2V4lsrCWAXA2u476+mB0Pm58UVEmgML7Vml0qlBi/cZisdVQbcnDJptRSBoM6iiX+owJmkcoZF5AgKY3Gw5W868dVsxWR3+tBpvMF0f0DIprvZ/C8iAOng3DqGtgUOwZtJqLpn2FBCG+6k5VyACqTVZe2qJkcHQSvxyTjZ/OsxWJw4dCKSqtsn+/doA/Awd1zvJxj9hC+vbsyfHs5h8mY24wogsyU1OsxWYF/56V7CjOJSkkHEny0Fp/rSChcptVQ4rv63UK2QVCKjOZHgSG69OvqiSxraHRuHnJUunEzdiDUSt8CdT2cbcYVyVCIfMGGvrz1vZdze52xtK092Rv/pZhBRqjKJVSD8b31zPjumOoVQ3YbFBU1XU3sh/O1bJkfQ+enJxHgG9V6we4iX79Suh5KJCySgspA3SMH5/daZY9SYK0ITaOZze9v1eMAZ++eaCQ8f05wvqCImOVVai8UiFTI1PuvuET4pC/7VpvLFnlQ7m+D4FVR0Du+AvQ2VJPy8flXhRuLSOmArkGcH/uSIH3IXzIvIBwfx0BuubfgE+dN2G2NK9bHz4bx4YfHPdbZdh8pJY3v0jEbFGRVRRNraVzrWOXU1hl5qVN0VTVee7NKzC4knkPneGPv83jlltOodF07m8U17PpZJLhIToSJ5xHUjRtSzpe4X7PmfYg4d5yOLKPCWnI6C4dM99nIL/9MI5/F01AVl2Z868tFPpdy64jYrnyUv67XklFpT+yCx9vMpJz/WlvBGWoy8YVXF0IC5kXkFtWS0Vd89arKpOVPSd7Mar/cXb81JfSGhW3DjkCQEmVkZe3KLhgGbuc78/WsvS/fWiwyc226UzyKkz846uePDHxiFf4lHU2Bv8awoMDr8h9ZjbbkGRls1FQXxfkkRgQhVKqo9Hec1FBs9h8KTcp0alAq7SiVnjOMrGM+4MS5MH9YP/XXWYlC1ac5/dTtWw/buSgPIJBtD2HkdU3jO0lg1m9RYOItnRk7QcFrP0AfA1Kxt4cwvWjfQgLq0LCOcuZTdbw3R4NtTU21GqJr78s58SxxmvmurQApt9hJCK8AhmJ/Hx/Mr6oxWqVGThIz6BhKpTiqSpoJ+JPx8OpNjWwdOuxVn1sVu5qIPNsEvtzalEqGhiREERYQCl+PjVAUIvHZrWQ+LQrOJhXx8mCaPpEnmu98VWARnXlm3hZpYmzO0OJHnUOqZkX9YJaFXqVP1/lnUevUhPtq+dsdQ05NY4RoQMCgrk+QoNCcneGfx1wZcLhLkdlQkoeDgf3uLTbc4brCFacx6fS0UdNW3mGPpwhO3QC7+8wkHy9GsnqvLtAhnk872/RCEf+VqiptrJ+bSHr18LgIf48vkCHUtH6S+frr9Tzw/6m8z7u+bacPd+WM/kXYZzJqudg5sWEqts+g2V/u4bIaKPL5iC4uhAKmQfzzcliFm86QkV9Q6ttrTbZHn1ptcks+W8w1/eOJL8CoLbFYz2BLQcDrmqFrKYhFFmWaLApGXSdkuj8AOrrZIxBEjXVUF5qxWKRKfu+B4FDcpu0Jm7IyXH4nl3ddILMI+UlKKUQRkZ0xkycR8IH2RMUMoCE3q5VyBRKXvkslEHxIdybUIJkcswVJ6t1rN2mxmqVKNQPJqJqn1Pdyiot//lCKGNt5Yf9lezc4ceo0a0rZOVlrSvH//34SoVN76shIMhz3S8Eno9QyDyUGlOD08pYU1TWN7DpUPuOdQfZpR6QzNFNnK/rwcGy4osboiDwklJxesDVXilHy0oYGRGE1eaDRVaiVdQjSV17DmQPyBh1ATlED0FhSKUdr4ghq7TsNF1PVa3Et4clDp8ZzZ8nHkVXecreRrLU8cC4Ov6xRc8nB8P5VU/n+pYaTEwc1sCnu0RUZVtpcPJ2GN3DhzOn2/6icMc9Keha8PX1Fuoaaimuz6fBZkal0BDiE4lOJRTNrkAoZB7KO9/ltFsZ80bKaixU1+sx+Hi+Nc+VWGUNR8rLunzcBmQ+yqrlfH1jEIGfSsMdCeGouzQfmPv9x+wozEjXjoRtH3eomzr/BP6ysz8nLzH2llfD7zf04w+3BNEgKzDblNSYNWzZ35iMed8xkBMNSCbnfo+cYhFV2R4O7K9i1A2+qJSNypYMmEy+qFRWFAorDQ1qKivUnM0ubFf/PROCXSht11NuKuFkxUEK63IdXpYkJMJ1PehtTCZA691z9HRElKUHciS/kpW7nS/22h2wyvDcJzGcbiKT/+nCaL4/3Qub5xhUXIbZ6ofVBakP2sP5+otWgKoGM2uzipDlrnpH0wOe9cIhxwcj+7SvYoWs8eWM7wgWftLPQRm7QG29xDMfhfPculCWfRLE/9tk4Exh47KjwQcud8wvNw5kXenN7GgYx3n/FGy6Rj9Qs18sh7PEcmV7qKm2Iv2cEkOW1ax5X81Dc87xwN0F3DfrPHNn57HgkTOczWmfb2X2qaYjpL2B/NocdhZspqDu7BWWaxmZgrqzjftrc5rpof0sXrwYSZIcPhERF/0p1q1bR3p6OiEhIUiSZC8Kfikmk4lHH32UkJAQfH19ufXWW8nNdfSdff7550lLS0Ov1xMQEHBFHyUlJdx8881ERUWh1WqJiYnhkUceobLyortBfX099957L8nJyahUKqZNm+aqnwEQFjKPw2K1sXjTUazdo8RomyiqNvPaVh2LpgYQ4l8OQF5pKEv+q8EmywTo+hDkqyLEV8H0YQVEBHjvDfACNtlzrB0VZhPnanT0MHR+XjgJLbKn+TZKFqQpd8KHK51qbtMF8l3NtXx91IcTubTbr+uFKceRKquw+RixKX1Q1pfy9ndxHM6WaLxFRwPRxIZBcYWMuUEoZO1BoYCML5WcyVJyYH8ZleWufSHYtvEYN6b3dWmfXUG5qYQD57+xV4RpDhs2vj//DWkRN7vcUpaUlMS2bdvs3y8tCl5TU8PIkSO5/fbbmTt3bpPHz58/nw0bNrBmzRqCg4NZsGABkydPZv/+/fa+zGYzt99+O6mpqaxYseKKPhQKBVOnTmXJkiWEhoZy8uRJ5s2bR2lpKatXrwbAarWi0+l47LHH+Oijj1z5EwBCIfM4Pso8x+kSz0lL0NVUmaz8eUMoIxOi0apkvvjJgk1uvHGW1zVQXtfA6WL47ow/L0xXEBV0Zf1Jb0GWocyscbcYDuw5f54eBh10sn+X7GQKgq5GDpSRJt4On33YcjuFir8fTmP/iY4rRz9V96CkLp7PdqiprAG9FmpNV/abUwQixUX7OX60huNHO+/empAY0ml9dyYnKw62qoxdwIaNk5WHGBp6g0tlUKlUDlaxS5k9ezYA2dnZTe6vqKhgxYoVvPvuu4wbNw6A9957j5iYGLZt20Z6ejoAzz77LAArV65ssp/AwEAefvhh+/e4uDh+/etf8/LLL9u3+fr68uabbwLw7bffUl5e7vQcnUEsWXoA56tMlNWaKa8188+d2e4Wx+1U1DWw6VAtH2fWUdmCH90rmwM5ez68CyVzLWXmKI5XFLfesAs5X1+HLHeFY7LnvnTIMXqYejdyYFizbUyGGJcoYwBvfObLv7/WUFkjAVKTypjA8/HGCMu6hloK63Jbb3gJhbVnqWtwrXX7xIkTREVFER8fz8yZMzl92vnydPv378disTBhwgT7tqioKAYOHMjOnTvbLVNeXh7r1q3jhhtcq3y2hFDI3MzWnwq59R87mfjGt/xi+W7KW0gAK3CktNbCmxmBWBq69s+43qzB5ALLVn0Xy+0sBXUdyx7fOr54mv/Y5cjhKpgxtdn9PpVZPJjuYUuuAvfihW4mxfX5bY52lpEprs93mQzDhw/nnXfeYcuWLSxfvpyCggLS0tIoKXHOJaWgoACNRkNgYKDD9vDwcAoKCtosz6xZs9Dr9URHR+Pv788///nPNvfRXjzziXCVkFNayx//ewSLVabBJlNl8uyHlCeSV2FiU2a/Lhvvm6N9+fW70Sz4dyw55zuWyEut9Mwb+PozOVjl9jm3O4OEZy3TNovCDNNnw8BhyD6+DrtktY6B/mdRSJ55DgVdT0G+59bkbY4GW/vq3zbYXGc4mDhxIjNmzCA5OZlx48axceNGAFatWtWhfmVZRmpH+ZfXXnuN77//nk8++YRTp07xxBNPdEiOtiB8yNyEucHG4k1HsHbH0MEu5tMf6hjSM4weIR3PIdUS24/05e2djTeiapOVN74y8vtJtRj1lWQVRZMQ0bbEtp66MKVEQtFMiSbX4Jn+Y00hhyggZACkJoFJA8Xl5OwtZukHOixWTz2DAndw/Ejn3n86A5WifS9HKkXnuTX4+vqSnJzMiRMnnGofERGB2WymrKzMwUpWVFREWlpam8ePiIggIiKCfv36ERwczKhRo/jTn/5EZGRkm/tqK8JC5iZe/fIEP+ZVtt5Q0Co2Gf76ZSCWBte/X2w72I+KGgM7j/WxK2MXKKg08+RHoTz3aX+WbtJyPC/G6X4brDqOVXjmG/U1IWFIUvvenLstkozsY0KO9mXZf3yxWCUUSlB4TpCswM2Ul9Vh87IX7BCfSKQ2vhpKSIT4dJ5yYjKZOHr0qNMK0JAhQ1Cr1WzdutW+LT8/n0OHDrVLIbsU+edlaJOpa+o8CwuZG9h3poy1mVdvmaDOoKDSTFZRJH2jzrqsT0uDivU/WHlvTyjN+TzVW2xk/1wL9K0MHb+bFIy/rjHBp17b/EVc1RCIyVrqMlldSVKgFuhMhcyLLUuSjRf/EUt5iYLo2DqQbFRV6FnwQLa7JRO4megYIwqFd/1t61R6wnU9KKhz/r4Zro9xaeb+hQsXMmXKFGJjYykqKmLJkiVUVlYyZ84cAEpLS8nJySEvLw+AY8eOARctWUajkQceeIAFCxYQHBxMUFAQCxcutC+BXiAnJ8fel9Vqtecz6927NwaDgU2bNlFYWMiwYcMwGAwcOXKE3/3ud4wcOZKePXva+zly5Ahms5nS0lKqqqrs/VxzzTUd/i2EQuYG/v6t8xEkAufZcdyfvlGtt3OGksoA3vwqksp655NEltZa+MNaf8AfvVrJ3NE2UuKvPNcNNh9OV3XNG1dbCfXRoVN1ruXOU1NeOIvBrxqD38XvVRXe9RAWdA7RMd5ZVLy3MZmiunNOpb5QSEp6+w906fi5ubnMmjWL4uJiQkNDGTFiBLt37yYuLg6A9evXc99999nbz5w5E4BFixaxePFioNHvS6VScccdd1BXV8fYsWNZuXKlQz6zZ555xsEvLSUlBYCvvvqKMWPGoNPpWL58Ob/5zW8wmUzExMQwffp0/vCHPzjIO2nSJM6cOXNFP7ILgjok2RW9eACVlZUYjUYqKirw9/d3tzgt8vcdp/lgfy7Vwonf5dx2rQ+TrjmKooOL8QfP9OR/t3bsQTtlkI4Z1x2xf5dlqLJEcLisjjqrZypkepWK2+Kj0as6azldDXSfSOIGi45lT5dy5pSIuLzaGT02gQce7dgSWWu09Jyrr68nKyuL+Ph4fHx82tRvQW0O37eSHFaBgmtDRxGhj22X7Fczzp4b4UPmBh66vhdfPjaK9+4ZhsrLTNyeztrv63lp4wAyjiR2KAoyKSab8f31jIhvv2neR+X4rlNhjmJfcbnHKmMAtQ0NvHcih3qrX+uN24GEoVP6dRfvvlUnlDEBAA1W77VtROhjSYu4mQh97BU+ZRKSw35B5yGWLLsQmyxTWd+AQatEpVBwsriaBi9zAvUGfiqs46dCAB2Pj+3V5LJhaygUcPfIw9hkKPq0P6eL217fbl2miX5RjtGXSkmBVfbsJTsbMv85nceshAjUCtclcJUwItP1hdQ7i6M/GtiZcXXVnBU0T0WZdyvmAdpghobeQF1DLcX1+TTYLKgUakJ8Il3qMyZoHqGQdSEPffA9ueV1aJQKYoP0fH+23N0idXsq6xrDs+vMGrRqM201SErQ7qLmVpvM/36u409TwrCoNZys9Kys/C1R29DAxpwypvV0Vc4wCZlqF/XlfkqK/HnjJaGMCS5SXOS51Sfagk6lJ8aQ4G4xrkrEkmUXMjQ2kPPVZs5V1LMrqxRTg2dbSroDFXVKzp4P59H3erDuuwFtPn7fqQR7FGV7qDNbOVym8Cpl7AIFdTXIsmsUMgk/6NTcZl2HLCt5561i6uvE9Su4SPqt/d0tgsDLERayLmTO8Dg+O1JIbnmdu0W5avjskIkvfvKnwdbAfw/WUW9JYky/85TW+GLwMWHU1ZJ5JoK92QpG97Xgr7NQbWq0qhm0Fv69T0lHEplGGrUofFxXZqSrya3REmNwRQqM7nOr2Z2h4cgP3pcEVNB5hIYbuDG9r7vFEHg53ecu6QX4qJWM6RPCe3tdlytL0DJ1Fht1losK1bafatn204UyONqfP41O9o1+ZxIXc45JdDQisLDShGwyImkrOtSPu9h4NodbY2OJ8u1oKozuY00KDBG3TYFA4HrEkmUXU1jpuRF2AtdjleGTHf5Y60LcLUq7yarybmdlVyDLSmqqDNTVGlCK7PyCyzhfWM03X5zk6y9OulsUgRcjXvW6kGpTA1+f8j5fIkHHqDI18N9dOqaM9EOh9cxySS1xqqqckRH+wNUZESzLCpY9VcPp42KZUtA8//rbboamxjJ6bG93iyLwUtpkIXvzzTcZNGgQ/v7++Pv7k5qaymeffWbfL8syixcvJioqCp1Ox5gxYzh8+LDT/a9ZswZJkpg2bVpbxPIaMnPLhSP/VUpFfQNbvwtCtvi23tjDqG1owNZB537Zi8sl7d7uw+nj3SOCTtC5WCzeH7hSbanlSNkpMkt+4kjZKaotwkLeVbTJQtajRw+WLVtG796NbwCrVq1i6tSpHDhwgKSkJF566SVeffVVVq5cSd++fVmyZAnjx4/n2LFj+Pm1nGjyzJkzLFy4kFGjRrV/NgKBB1NYZea7H8O57trTSF6kn/golCikji21S8hea187cVQ8kATOUV7qvQFbhXUl7Dt/mKzKXGyXXK0KJOL9ezA0NIlwXbAbJez+tMlCNmXKFCZNmkTfvn3p27cvzz//PAaDgd27dyPLMq+//jpPP/0006dPZ+DAgaxatYra2lpWr17dYr9Wq5W7776bZ599ll69enVoQp6MVSSBveo5VlhHTWmcu8VoE75qdYf7kL045YVWK1xtBc6h9fFOL6BTlWdZe/pzTlWedVDGoDFR9KX7Xc3ixYuRJMnhExFxscrKunXrSE9PJyQkBEmS7MW8L8VkMvHoo48SEhKCr68vt956K7m5uQ5tnn/+edLS0tDr9QQEBFzRR0lJCTfffDNRUVFotVpiYmJ45JFHqKy8WEYuIyODqVOnEhkZia+vL9dccw3vv/++y36Ldt9prFYra9asoaamhtTUVLKysigoKGDChAn2NlqtlhtuuIGdO3e22Ndzzz1HaGgoDzzwgNPjm0wmKisrHT6eTq3Zex9KAtfx2fcNyBbvyXxdaqqHDi85eueDCqC6Sly3AudIGhzpbhHaTGFdCZvP7mi1gohVtrH57A4K60pcLkNSUhL5+fn2z8GDB+37ampqGDlyJMuWLWv2+Pnz5/Pxxx+zZs0aduzYQXV1NZMnT8ZqvXjtms1mbr/9dh5++OEm+1AoFEydOpX169dz/PhxVq5cybZt2/jVr35lb7Nz504GDRrERx99xI8//sj999/PPffcw4YNG1zwK7TjLnnw4EFSU1Opr6/HYDDw8ccfM2DAALvSFR4e7tA+PDzcoTL65Xz77besWLGiSa23JZYuXcqzzz7bVvHdikLUrRTQmIojNzeKmHjviMiK9vWj4w793rns12DR8eP33ptHTtB1hIT5Mnl6krvFaDP7zh92upybVbax7/xhbokd7VIZVCqVg1XsUmbPng1AdnZ2k/srKipYsWIF7777LuPGjQPgvffeIyYmhm3btpGeng5g1xdWrlzZZD+BgYEOylpcXBy//vWvefnll+3bnnrqKYdjHnvsMbZs2cLHH3/MlClTWp9oK7TZQpaYmEhmZia7d+/m4YcfZs6cORw5csS+X7rMOUaW5Su2XaCqqor/+Z//Yfny5YSEtC0twJNPPklFRYX9c/as5+f2sliFQ7+gkW+P1yI36NwthlMMCgrs0PESRi7kevMaZIk3X7Ly8MxcaquFhUzQOtcM7cGp48X8e9X32LzEPaXaUsvpytzWG15CVmWuyx39T5w4QVRUFPHx8cycOZPTp52vP7x//34sFovD6lxUVBQDBw5sdXWuJfLy8li3bh033HBDi+0qKioICgpq9ziX0maFTKPR0Lt3b4YOHcrSpUsZPHgwf/nLX+zabUFBgUP7oqKiK6xmFzh16hTZ2dlMmTIFlUqFSqXinXfeYf369ahUKk6dOtWsHFqt1h7teeHj6RzM8/xlVUHXYLbKHDwahewF9+3wDuuNXuiDJcmUlnQsKbDg6qK0uAaLxcqmjw/zl6UZmOo9/+8npzq/zeE2NmTOVhe03tBJhg8fzjvvvMOWLVtYvnw5BQUFpKWlUVLi3NJoQUEBGo2GwEDHF8fw8PAr9BFnmDVrFnq9nujoaPz9/fnnP//ZbNu1a9eyd+9e7rvvvjaP0xQdvlPKsozJZCI+Pp6IiAi2bt1q32c2m9m+fTtpaWlNHtuvXz8OHjxIZmam/XPrrbdy4403kpmZSUxMTEfF8xhkWeZAbrm7xRB4EJlnazFXRrtbjFZRSh217HqB1tkE0bE+7hZB4EV8/10uK/66C4DMvbn8Zel2j0+DYba1T2ls73FNMXHiRGbMmEFycjLjxo1j48aNQGMWh47Q0upcS7z22mt8//33fPLJJ5w6dYonnniiyXYZGRnce++9LF++nKQk1yxVt8mH7KmnnmLixInExMRQVVXFmjVryMjIYPPmzUiSxPz583nhhRfo06cPffr04YUXXkCv13PXXXfZ+7jnnnuIjo5m6dKl+Pj4MHDgQIcxLkQ/XL7d2zlVXMPpYpHLSODIpn0Kpl4fgEJb7m5RmkUpdezmK3tp2aTiIi9bZhW4ndLii0t5h3/IZ/OnR5hyW7IbJWoZjaJ9EdTtPc4ZfH19SU5O5sSJE061j4iIwGw2U1ZW5mAlKyoqatYY1Fp/ERER9OvXj+DgYEaNGsWf/vQnIiMvBmxs376dKVOm8Oqrr3LPPfe0eYzmaJOFrLCwkNmzZ5OYmMjYsWPZs2cPmzdvZvz48QD87ne/Y/78+fz6179m6NChnDt3js8//9whB1lOTg75+Vefk2yvEF9enzGIUQkij4vgIlWmBjbv8Ue2eV7AR7DWhzGR0UhS+4uLS/gD3ledAOB8gVDIBO1DkuBPL95MRJRnu9LEGiJRtDGCWoFEjKFpB3xXYDKZOHr0qIMC1BJDhgxBrVY7rM7l5+dz6NChdilklyL/7FNiMl28F2RkZHDLLbewbNkyHnzwwQ71fzltspCtWLGixf2SJLF48WIWL17cbJuMjIwW+2guAsLbUUgS1yeEkBofzKyV3wlrmcBOcbUFrD6g8JykknqVitvi/ZCkjjnvytTjjUuWmXt8KS12fXi/oPsTEKjjf+YOo3diqLtFaRWDWk+8f4825ReL9++BQe26tD0LFy5kypQpxMbGUlRUxJIlS6isrGTOnDkAlJaWkpOTQ15eHgDHjh0DLlqyjEYjDzzwAAsWLCA4OJigoCAWLlxoXwK9QE5Ojr0vq9Vqz+zQu3dvDAYDmzZtorCwkGHDhmEwGDhy5Ai/+93vGDlyJD179gQuKmOPP/44M2bMsPuoaTQalzj2e6G3rXejVEiEGjpWhkbQ/ZBtnpWna3BQKJLU0MFe1ED7rWvuIue0P397KcfdYgi8lBGj4xmW5j3Jn4eGJqGUnFMFlJKSoaGuTe2Rm5vLrFmzSExMZPr06Wg0Gnbv3k1cXONvuH79elJSUrjlllsAmDlzJikpKbz11lv2Pl577TWmTZvGHXfcwciRI9Hr9WzYsAGlUmlv88wzz5CSksKiRYuorq4mJSWFlJQU9u3bB4BOp2P58uVcf/319O/fn/nz5zN58mT++9//2vtYuXIltbW1LF26lMjISPtn+vTpLvktJFn2hjiv1qmsrMRoNFJRUeHREZcHzpbz4Affe6HNQNCZ3DXGgkrvOYXn+wUEMSayY3+lEkZkKlwkUddgs2r5zb0F1NZ6p9+boGuJ7RnIPb+6jvq6Bg4eyOObbSeZfNtAbpneOT7QLT3n6uvrycrKIj4+Hh+ftgWknKo822pyWKWk4OaY60nw7z7Bdl2Fs+fGs17LuznVpgYWbToilDHBFeQVBBDby3MUsmPlZVwXei3+mghAQpaLsMklyJS2oRfvMsDLsoJ33zIJZUxwBX5GLc+8OJFVb+3hUOZFH+ibJvalT78wAJJTohh1UwJ+Ru+Lzk3wj+G2XhNELUs3IxSyLkKWZZZ9foy8inp3iyLwQLb/VMPtwdH4GM+5WxTUChW395pAgPaSvD6SEdkmI8vOK2SN/mPew9b1anZ8meduMQQeSHVlo1P3I78bzcvPfsGpY8X4+mkYMaqnQ7uYnh1LouxOwnXB3BI7mmpLLWerCzDbLGgUamIMES71GRM0j3e9wnoxH2WeY/PRQneLIfBQZKCisvPfrOP9erTaxkepJVgb4LDNasvBJrel1JMP4DlBCq1x6pgfH74jlDFB08gy/GVpBjYbPPaHMahUCgYkR6LTdz9/YINaT//AXgwOTqR/YC+hjHUhQiHrAjJzy3nlC+dyqgiuPmICfZg2VEtYj+YrU1yKwkkHXGhcbugf0IubooZzV+9JTI4djVbR8kOkylLD8QrH+rMybYs4lPCOslAXOJLpPcqjwD3kniln86dHCAjUERCoQ60Wj0+BaxFLlp1MQWU9v/vkIA1eUttM0LVMHaLFPyyL1hJKK5AYFNyXoaFJaBQaTlbmcL6uFJDw1/hiUOsxqPSolSoUKKhpqKXMVEWsIQJ/jcGhrzBdEGdrWi4pcqTsFIkBPS+OL0Vjk53PHyjj2RnKL2fQED3r/+NuKQSeztdfnGTgNZHc89BwwiP9Wj9AIGgDQiHrRGyyzDMbj1Ba6/k1zborOrUCc4MNqwfqw6MTfTGGNy4DyjYJSdG0kIFaf9J7jCRMdzHPTb+AePoFxDfbd4DWj2jfpmvI9jHGtaiQ6VU+DAzq47BNIhSJYCctZRLelgw2OMwD/0AEHkd5aR0vPP05D84fyeBozy97JvAuhELWifx9Rxbfny13txhXBT0CtATqlRzMa0xkGuyr5rbrLESEnqWkLIK/blW20kPXExfb6LMky7D/h14E+EokJGQjKRvzf6kkJcPDBjE4OBGVwnXy9w+IZ2dhJvXWKzPRqyQlPQ1RaJWOpVEkSUKp6EODzRmFzIC3KWRr3/UueQXupbiw2t0iCLohQiHrJNbsP8uKXdnuFsPjGNXHl8Hxlaz6WktVffOJR1UKibtSVfx4Rk1mbi03D9QTbjRTXa+msEJBqL+Nj7+/6Pcza1QJOp8KRhTHUFuvIi4iH42mMcov0L8IcK4MR1dSWBBJePRprHUhHMmvRSFBQrwGlA3oVT7MiB9PoNb1OfWUCiWJAT35oaQx43W8XzRBWiOFdSXk1Z7HoNYTa7jy95IIRMIfmcoW+5dQe1Vql/P5Rr798rS7xRB4ESq1573gCbwfoZB1AjtOFfO/wonfAa1KwaRBWpITjqNQwMjefdh8yFEhU0iQEKpDp5ZI61dLREg20aE+FFVFcb5SYkRSo6P5hVK9UcERHMv1R6uW0evOIUkQHXZlCZDcohigo1nnXc/nB2tRHY60+xfaZDhfGIm5QeKe4dGdooxdoJdfDwprS7ghcijh+ou5hWob6iiqK2vyGEmSUCmGYLF9BzRf+kv2ouz8CimByjIjIBQygfPofTuvuLa7KTfV8lN5AfVWCz5KNf0CIgjQikjLrkAoZC7ix3MVKBUSRwuqeD3jhFdZCDoTrUrB9KFqekbkodVezEuV3PM8u08ZqahrIH2gnt6RVfj7laFROy6jabX1/HJCFlbrlTfA0KACQoNadk6XZdh6UIknKmTAFcEem39sXHK96xpDU81dRowhoskCwXqVjp5+zUdISpIOtWIEFttOmk5roQa8ZTlHjVLqRe9+Cq4Z1oPMvbnuFkjgJVR2w3ySZ6pK+Dz3MAfLzmG7pICPQpJIDoxmQo8k4vxEYtjORMTtuoAGq43nPjvKnHf3sWzrMeotItP3BVJidSTGnXZQxgB8fct59JazPDX9PCOSThASVHCFMnYBhUJGrW6f1aXeZCC3vOl+L6BRStwxzIdf3qDg7lQND90I949WMmOIDxplK+GPLiRIr2ZobADBvhr2nmnaSuUJSJIWteJ6lNJgJAIc9+HrHqHajAqVIgVJUqNWK3nkd6NRa5RIConxtyTSq4948Aia5+RP590tgkv5oeQsrx3cyg+luQ7KGDQGp/1Qmtu4v8T5IuTOsnjxYiRJcvhERFx8WVy3bh3p6emEhIQgSZK9KPilmEwmHn30UUJCQvD19eXWW28lN9fxBev5558nLS0NvV5PQEBAk7Ls3buXsWPHEhAQQGBgIBMmTHAYr76+nnvvvZfk5GRUKhXTpk1zwS9wEWEhcwFrM8+RXVrrbjE8kpbUGaXShlLZuctbanUdd40IJfOMiiP5V56jmEAtt6VWYPRr2joikcDa/Y3KpEKCm/r5svNkPbUW16Z10KuVfPJgKnqNipIaMz4qz35XkiQ1SikahRxymbWs6xTYjqCU+qCQQuzf1WolM+8dQnikH8kpUciyzLHDRezZkc2ur7OoE5HSgm7KmaoS3j72LQ0t1LEEaJBtvH3sW36TPN7llrKkpCS2bdtm/35pUfCamhpGjhzJ7bffzty5c5s8fv78+WzYsIE1a9YQHBzMggULmDx5Mvv377f3ZTabuf3220lNTWXFihVX9FFVVUV6ejpTp07ljTfeoKGhgUWLFpGenk5ubi5qtRqr1YpOp+Oxxx7jo48+culvAEIh6xC5ZbU8t/knfsj1rgLKncGwnr5EB9rYecJKUbWZEF81Q3pqGJqY7Va5VEorfeOy6BsH5RUhFJX7UVWnwiZDXGgNIUGnUbSg+wxIOMVjIWGcK/YnLKCW8JDjlNf2Yd8Z1yrgfj4q9JrGyzHY13uyf0uSFqUUg1U+Dvh4TTFxuYnl1nGTEu3/lySJfgPD6TcwnFn3D+X/lmZw8IDI5C9oJCK68/w7u5rPcw+3qoxdoEG28fm5I8ztN8qlMqhUKger2KXMnj0bgOzs7Cb3V1RUsGLFCt59913GjRsHwHvvvUdMTAzbtm0jPT0dgGeffRaAlStXNtnPsWPHKCsr47nnniMmprGA+qJFixg0aBA5OTkkJCTg6+vLm2++CcC3335LeXl5e6bbLEIh6wBvirQWKBUS94xUEhd1HIBBvRuLNCuVnrdsG2AsJsDYtgLeCgmCAooICiiyb0vpVc/JIhXDe2nIKZE5WtC2LO/BvhoWT+pPUqQ/O0+X8I9vs/DzUXO+ykSon7ZNfXkCCqknNrnmZ2XMO3xrFJLzNQc1GiVBIcKp2ZPxNWjo1TeEg993jdI8ILlp5cHbKDfVcrC0bfVzD5bmUm6qdamj/4kTJ4iKikKr1TJ8+HBeeOEFevXq5dSx+/fvx2KxMGHCBPu2qKgoBg4cyM6dO+0KWWskJiYSEhLCihUreOqpp7BaraxYsYKkpCTi4uLaNa+2IhSyDvDDuXJ3i+B2EsN1xEVdjChttDZ5njLmSqLDzjL/1sb/D7Vo+dtnEZTXtS1oIDnKiEGr4uYBEUzoH44EWGXvDAWRJBUqxSAstq/cLYqTqJAIdbr1ubPlbN/aljqegq6gV59gZt0/FINBS4PVRmS0P4/N+ZDaTlhe9vXTcO11MVw7PIaAQB3xvbuHj+FP5QXY2hiCZpNlfqooYESYcwpTawwfPpx33nmHvn37UlhYyJIlS0hLS+Pw4cMEB7f+OxcUFKDRaAgMdHzJCg8Pp6Cg5aCvS/Hz8yMjI4OpU6fy5z//GYC+ffuyZcsWVKquUZWEQtYB0uKDWffD1bmMEeKr5oZ+Koy+LTvMd3fUahNzx5WzcW8oR5y0lJXUmHlq/SH+cttgJElC8XPdJFVr9ZM8GhvgHX8LCikGSXL+1hcYJKxjnoZer+YPSyag1TqeR42P6gqFbOK0AYwc04vKinoK86tIGhzJN1+eZMOHh1odJ+W6Hvzy0TQMXmi5doZ6a/uU1/oG1ym9EydOtP8/OTmZ1NRUEhISWLVqFU888US7+5VlGakN99S6ujruv/9+Ro4cyQcffIDVauWVV15h0qRJ7N27F52u8+vzCoWsAywc25fD+ZUcK/KWMH/XMDROT/qQM+2OfOxu+OoruG10BTl5cWQcVZFd0vqy3c6sUj79MZ9pg6O6QMLOR6YavCDZi4Q/Sqltb/Y6vRqFQsIm6tF6DNeOiL1CGQOwNjha55VKiVtvT0b/s19m0uDGhMfTZ11DSKiBnOwyvth0zN4+IFBH4sBw9nyTDYCPj6rbKmMAPsr25VPzUXVeHjZfX1+Sk5M5ccK5XJ4RERGYzWbKysocrGRFRUWkpaU5Pe7q1avJzs5m165dKH52LF69ejWBgYF8+umnzJw5s20TaQdCIesAGpWC/hF+V4VCNmGALzUmCDfaGJhwokVH+KsRhQQ9o89wbzR8urMPB8627vT/169PMTk5AlW3+DE9M8/b5SikaCSpbQ/Y0uJaoYx5GLf8IqnJ7fOfvpHtn5/gm69Oo1BIpI7qaVfGLkWhkBgzobFea2lxDQe+a4yynn7XYAYMiqBv/zCGXx+H2eTaaGpPo19ABApJuiLVRUsoJIl+xs7zoTOZTBw9epRRo5wLHBgyZAhqtZqtW7dyxx13AJCfn8+hQ4d46aWXnB63trYWhULhYFW78N1m6xo3HKGQdZAfznlHVFl7eXgsvP+tiujgeuKictwtjlcwsn8VB842XVpFpZDoE2qgsKoeU4MNyUvSRLRGY1klP2QPr2EpSW1bfqyrs/CXpRmdI4ygXfj5a4mKMTa5r3diKL0TQ7n7l8PQaJQolK2/7PQdEGZXyPyNPoSG+zlE3HZnArR6kgOj+aHU+aTIyUE9XOrQv3DhQqZMmUJsbCxFRUUsWbKEyspK5syZA0BpaSk5OTnk5TW6Bx071mjRjIiIICIiAqPRyAMPPMCCBQsIDg4mKCiIhQsXkpycbI+6BMjJybH3ZbVa7fnFevfujcFgYPz48fz2t79l3rx5PProo9hsNpYtW4ZKpeLGG2+093PkyBHMZjOlpaVUVVXZ+7nmmms6/FsIhawDZJXUkFXSvfOP+RsqUEjB/GcP/PYX7pbGOwgJLKBvWG+OFzn6lN2SFMFvx/XFoFVhbrBRUFmPUtFNFDJJgUpxHQ22TGScKUDuDlRItK0CwvHDRZw5XdpJ8gguMHZSIrfeNpC339zTasWE667v2Wp/Pjrnl9SuGdqDf6/8nqTBEaRcF+P0cd2FCT2SOFyW51TqC7VCyYToAS4dPzc3l1mzZlFcXExoaCgjRoxg9+7d9sjG9evXc99999nbX1g6XLRoEYsXLwbgtddeQ6VScccdd1BXV8fYsWNZuXKlQz6zZ555hlWrVtm/p6SkAPDVV18xZswY+vXrx4YNG3j22WdJTU1FoVCQkpLC5s2biYy8WNt30qRJnDlz5op+ZBcEZUmyK3rxACorKzEajVRUVODv3zU5Yv61K5s3vuneNfCenFbG0k8CGdvPl1GDj7tbHI+nsiqIY7nBfH64Dov14qWllCQ+eXAEkcbOdwx1J7LcgMW2Dc+LtFWhlJJQKqLbdFROdhl/mv/fTpJJABDVw8ifX5+MSqWgqrKeZ57YSGnxxRddjVZJSJiBvLMVSBK8+MZUwiNde4//4O39JA4I49rhnq2QtfScq6+vJysri/j4eHx8fNrU7w8lZ1tNDquSFNyXOJLBwZ79G3kizp4bYSHrADuzPNUS4DoUigbG9vNlxIBsd4viFXy4K4CzZVdaTe9Pjev2yhg0psBQSJHY5LblNupsVIqhKKSgNh9XmFcJgDHAB1+DljyRBNrlTPpFEqqfK1P4+fuw5PXJ7NlxBrOpAYVSYtC10ej1av728jeERRhcrowBzLpviMv79CYGB8fwm+TxfH7uCAcvK5+kkCSSg3owIXqAqGXZyQiFrJ3YZJnjhd3XmT/MoGFCMqjVZmEZawODog2cKzcxMMpIYpiBDw+co1eIL/eN6Olu0boMpTQIUGGTzzTTQg0o6cokshJ+7TpuyIhY7p83goTEUA5n5rP6X/tcLNnVjVqtYMTong7bfA1abrq57xVtn3x+whXbBK4jzi+Yuf1GUW6q5aeKAuobLPio1PQzRrjUZ0zQPEIhayeyDPUN3TMC587rfOgbexqlslusZncZaoWGZycNZsFNFmwyBOjU3DsiDqOPGo2H16Z0JZIkoaQfNrmQy5UuCX9UimuwyUVY5Z8AA0qpJwopHIstA3D9NdWojFlpVATbhkIhccP4xmi8qB5GMvflcuRH55NNClrGYrFx6lgx/QaGu1sUwc8EaPUuS/oqaBtXz1PCxSgVEjf0dj7btyeiUkj0CvElIcSXSP/Gde0pg/T0jz8llLF2YLGZOVlxCD+tioCfnYrD/XzwUTcdcdmdkSTlz8uEPVBI0SilgagVo1EpRiJJBhRSGCrFENSKUSgVsUiSFoUUBviiUgxznRwYUSmuR5La5lNzObIsk5dbIRz8O4EP3z3gEodogcDbERayDrBkygAOnC3nmY1HKO2Ech2dgV6tZGy/MEYnhHBdXCC+lyRXPF9VTz35nKjMp7ah+y7HdiY/lR8gxCeSAK3wtVBI/iikQU3ukyTDFRGPSukalFKjhU0iEJmyDssgSX5tytbdHF9vO8m//ra7w/0IruTksfOsWfk9M++91iXnSiDwVoRC1gG0KiUj4oMJ8/PxeIUs3E/LrCExTBschaGJDNcAoX4+QDw6tY7dhVu7VsBuQpA2DF91+/yVrnYufRgrFX1psO39OUCghPb7m3V8ESDrZIlQxjqZzZ8eITTccNXk/xIImkIsWbqAMA8urSEBM66J5qNfjuB/rottVhm7lBCfCIK0YZ0vXDekp18iasWVmcEFbUMhBaNWpKNSDG63Qz6ARMedkUPCfAkKEU7Nnc2/V+6nvLR753UUCFpCWMhcgLENSQjbyqiEYEpqzBwpcD4D+qiEEAZH+1NR38DU5Eh6Bvu2edwwXQ9KTUVtPu5qR68S1jFXccFiplTEA72BBhpse9vaS4fl8PP34ZW//4LtW0+y6q09He5P0DRms5UTP51nWFqcu0URCNyCUMhcQL25c6ItjTo1S28dSINN5qEPvneqZmaIr4aXpg1E7UTJkJbQq9qW0VwASkmFvyaw9YaCNqGQQuz/b2t5Jklyzd+xUqngppv7UldrQZLgs0+OUFnRdWk7vJUhI2IYPa43YeF+rPjbLk7+dL7F9honLPiCzqWkto4fCouotTSgV6sYHB5GsL7751D0BMRfvyvoJD/UWwdG2iP0Xp8xmHvf20dJjZlRvUOorm9gb86VTs8jewV3WBkDsMneUSzak4gxJKCQhBdAZ6JUJGG1HflZKWspMk9CKSWhkFwbCX3L9Mai1jfd3JdTx4uJ7GFk2R8/pzDfs2t4ugNJIfGrJ0ah0TTew37/7Dg++feP/HS4EK1WRUODjcL8KjQaJSq1gtiegfRODGmlV0FncbK0jLVHj7MvrwCr7FhlZGhUBLf170vvIPHC2ZkIhcwF/H5cXw7lVZJf6bo35gCdmjnDY+3fQ/20vHFnCnVmK/0i/DA32Lj3vX0cv8RqppQkZlzTttIwzVHTcPEBE6QNI0wXTVHdOYyaILKrjiG3+DDs3uiUvvQw9MKgNmJQ+eOj0qNSaFBKV196i65GIQWhUF6PLFuxydlY5WNNtFKiUgxGIUV0mhw+OjVJgxvr202bOYi/v/Ztp43lrcg2mX+8/i13zrmW0HADGq2KO+651t1iCZpgd24er+7eh8V2Zekkqyyz51w+3+cXsiB1KMOjo1w69uLFi3n22WcdtoWHh1NQ0Jjvb926dfz9739n//79lJSUcODAgSsKeZtMJhYuXMgHH3xgr2X5xhtv0KNHD3ub559/no0bN5KZmYlGo6G8vPwKWfbu3csf/vAH9u/fjyRJDBs2jJdeesk+XkZGBq+99hrfffcdlZWV9OnTh9/+9rfcfffdLvktxOu8CwjQa5g6KLL1hk4iAc9M7E+A3tE5PC5IT7+IRh8ljUrBX2YMxt/nok5tlWVig1zjfByui6GvcRBjom4lLSKd3saBpEWkkxQ0jKGhNxDjm3BVOv6rFRpGRU4iMeAaon3jMWqD0Sp1QhnrYiRJiVKRAFwaUKNCKSWjVozpVGXscoamxhES2nY/zauBvTvPcC6n3N1iCFrgZGlZs8rYpVhsNv531z5OlnY8Hc3lJCUlkZ+fb/8cPHjQvq+mpoaRI0eybNmyZo+fP38+H3/8MWvWrGHHjh1UV1czefJkrNaL7kRms5nbb7+dhx9+uMk+qqqqSE9PJzY2lj179rBjxw78/f1JT0/HYmnMorBz504GDRrERx99xI8//sj999/PPffcw4YNG1zyOwgLmYtwJnrRWe4aGsPo3q2b7kP9tPQJNbD/bDnQuFzpKjkCtMHN5tIK18cQro/BJtvIqT5BXk32VRMAEKAJQaPsWJJRgetQSn2xydmAGqWit4O/WVeh0Sjp0z+U4vM1XT62NxDZw/W1JwWuY+3R460qYxew2Gx8dPQ4vx853KUyqFQqIiKafomaPXs2ANnZ2U3ur6ioYMWKFbz77ruMGzcOgPfee4+YmBi2bdtGeno6gN0Kt3Llyib7OXbsGGVlZTz33HPExDQWUF+0aBGDBg0iJyeHhIQEnnrqKYdjHnvsMbZs2cLHH3/MlClT2jTnphAWMhfx/c9KUUcJM2h5cGS80+31mouWmRDfrk23oJAU9PRLJFDr3RUL2oJV+NZ5FEpFDGrlKNTKEW5RxqAxi/+xw1fHC0l70OlFGhhPpaS2jr15bSsFtjevgJLaOpfKceLECaKiooiPj2fmzJmcPn3a6WP379+PxWJhwoSLtU6joqIYOHAgO3fudLqfxMREQkJCWLFiBWazmbq6OlasWEFSUhJxcc1H/lZUVBAUFOT0OC0hFDIXkRDiS7gL8pE9NibBIXt+awRcknLDXSV6/NQBbhnXHZSaiiiuF7UMBReRJInQCAMhob7MvHcIyquobmlrxPQMxM/fc/M0Xu38UFiErY1lq6yyzA9FLUfLtoXhw4fzzjvvsGXLFpYvX05BQQFpaWmUlJQ4dXxBQQEajYbAQMeAg0v90JzBz8+PjIwM3nvvPXQ6HQaDgS1btrBp0yZUqqafyWvXrmXv3r3cd999To/TEmLJ0kU8dH0vHhwZT0FlPUcLqzheWM2pkhpOna8hp8y5ZIfxwXrG92tfkV2tSsHDo9xTEPZqKxNUY6kixKfrfJQEns/jT96IRqtErVbiZ9Tyz//bydVcnlGtUXLr7cmMndhXlEPyYGot7bP411lcV5lm4sSJ9v8nJyeTmppKQkICq1at4oknnmh3v7Ist+lvr66ujvvvv5+RI0fywQcfYLVaeeWVV5g0aRJ79+5Fp3NM/ZGRkcG9997L8uXLSUpKarecl9KmV7k333yTQYMG4e/vj7+/P6mpqXz22Wf2/bIss3jxYqKiotDpdIwZM4bDhw+32Ofy5csZNWoUgYGBBAYGMm7cOL777rv2zcbNSJJEpFHHTX3D+NWoXrw8LZl1c0fw1WOj+Nsd1zA3rSe9m3H+lYDHbuiNUtG2m9eF9k/c1MelfmxtoTvXvUwLTyfOz7Gci0htIbgcX4MG9c8W6utvTOCOOddyteohkdH+PLlkArfenoyvQVjHPBm9un3PDJ2685Kh+/r6kpyczIkTJ5xqHxERgdlspqzMMdigqKiI8HDnDRyrV68mOzubt99+m2HDhjFixAhWr15NVlYWn376qUPb7du3M2XKFF599VXuuecep8dojTadjR49erBs2TJ69+4NwKpVq5g6dSoHDhwgKSmJl156iVdffZWVK1fSt29flixZwvjx4zl27Bh+fk1nMM/IyGDWrFmkpaXh4+PDSy+9xIQJEzh8+DDR0a5J4eBu/HzUDO8ZxPCeQTx0fS+q6i3UmK1UmxrYeLiA77JLuWtYDKOccOS/nNJaCy9MSWJC//ZZ1jqKTbZytvqkW8bubLQKHwK1IaiVWs5Wn8QmN0bsnKo4RIwhwc3SCTyZSdOSSOgTwtaNxzhfWEX2qVJ3i9Tp9IgNYORNvZhwSz9UbnKfELSNweFhKCXJIe9YayglicFhnec3bDKZOHr0KKNGjXKq/ZAhQ1Cr1WzdupU77rgDgPz8fA4dOsRLL73k9Li1tbUoFAoHq9qF77ZLgh4yMjKYPHkyL774Ig8++KDT/TtDmxSyy6MInn/+ed588012797NgAEDeP3113n66aeZPn060KiwhYeHs3r1ah566KEm+3z//fcdvi9fvpy1a9fyxRdfuFTz9CT8fNT4+TS+YTw+pneH+np5WnKbrWqupMFmIb/2rNvGdwVqhQarbLUrXBfoGzAYSVLgpzZyY9RUzlQd51TlEeqtrnVoFXRPEpPCSUwKR5Zllv1pKz8dKgSgX1I4YZF+fL2t+7zIBATp+PPrk1G48V4kaDvBeh1DoyLYcy7f6WOGRUW4NHP/woULmTJlCrGxsRQVFbFkyRIqKyuZM2cOAKWlpeTk5JCXlwc0RkNCo2UsIiICo9HIAw88wIIFCwgODiYoKIiFCxeSnJxsj7oEyMnJsfdltVrJzMwEoHfv3hgMBsaPH89vf/tb5s2bx6OPPorNZmPZsmWoVCpuvPFGoFEZu+WWW3j88ceZMWOG3UdNo9G4xLG/3WtcVquVDz/8kJqaGlJTU8nKyqKgoMAh0kGr1XLDDTewc+fOZhWyy6mtrcVisbQ6OZPJhMlksn+vrKxs30S8HHcqYwAapQ8+Sh31Vu8rChyhj6WvcRAGtREAk7Uem2zlq7xP8dcEEmvoY2+rU/nSLzCFcH0PCmtz3SWywAuRJIn7Hh7B93vPcu2wGCKiG9NA+OhUfL7hJzdL5xqGjIgVypiXclv/vnyfX+hU6guNUsGM/n1dOn5ubi6zZs2iuLiY0NBQRowYwe7du+2RjevXr3dwmp85cybQmJJi8eLFALz22muoVCruuOMOe2LYlStXolRetNQ+88wzrFq1yv49JSUFgK+++ooxY8bQr18/NmzYwLPPPktqaioKhYKUlBQ2b95MZGRjntGVK1dSW1vL0qVLWbp0qb2vG264gYyMjA7/FpIst8319ODBg6SmplJfX4/BYGD16tVMmjSJnTt3MnLkSM6dO0dU1MVMvg8++CBnzpxhy5YtTvU/b948tmzZwqFDh/DxaT7fU1PZfaExBNXfX+S96Spyq0+TWeIdWcoVkpJo33h6GvpS3VBJqE8UGqWjj8uPJbvJqT7BkNAbiNTHNtOTQNBxZFlm26Zj/HSokLPZZRQVVHlkIMAFRctma1q4kFBfnnjmJqJjArpQqquTyspKjEZjk8+5+vp6srKyiI+Pb/HZ2RR7zuXxv7taTg6rVig6JVP/1YCz56bNFrLExEQyMzMpLy/no48+Ys6cOWzfvt2+//KohrZEOrz00kt88MEHZGRktPoH9eSTTzpEYFRWVtqTuQk6H1m28V3RV5yvz3O3KE7hpw7kurAb0akagyqMzUSG9vIfQG//JPTqpn0eBQJXIUkS42/px/hb+gFgtdrI2HKCNSv3YzZbWzna9fSIDSC3iaz6dz0wlGuG9mDRwo3UVJnt22N6BnLjhD6MHt/bHtAg8E6GR0fxwk2j+OjocfY2UctyWFQEM0Qty06nzQqZRqOxO/UPHTqUvXv38pe//IXf//73QGNOkAvmPXA+0uGVV17hhRdeYNu2bQwaNKjV9lqtFq1WRPC4D4k6q/dkJu9jTLYrYy1hUAvrqsA9KJUKxk5KpHe/UJb98XNqa12XWqAlevUJZtqdgxmYEsn8+z+isuJiTV5/ow+jx/VGq1Ux6Npodm3PYsCgCG69PZl+A8NFSotuRO+gQH4/cjgltXX8UHSeOosFnVrN4LBQl/qMCZqnw3kSZFnGZDIRHx9PREQEW7duta/Nms1mtm/fzosvvthiHy+//DJLlixhy5YtDB06tKMiCboASZJIChzGnqJt7halWfzVgYToIonUxxGodU8Wd4GgrcT1CuL2e65l1Vt7On2sKbcNZPqswSiUjalcxk5K5JM1PxAR7c+ga6O5Kb0v2p/T6cy4azCDr41mxOieQhHrxgTrddzUU7hruIM2KWRPPfUUEydOJCYmhqqqKtasWUNGRgabN29GkiTmz5/PCy+8QJ8+fejTpw8vvPACer2eu+66y97HPffcQ3R0tN0h7qWXXuJPf/oTq1evpmfPnvaoBYPBgMFgcOFUBa7GV+WZ58dX5c/w8LHoPVQ+gaApbFYbf/zNf4nqYaSqwtT6AS7ghvF97MoYwLQ7BzHltoEolVfm2gsN9yM0XCzlCwSdRZsUssLCQmbPnk1+fj5Go5FBgwaxefNmxo8fD8Dvfvc76urq+PWvf01ZWRnDhw/n888/d8hBlpOTg0Jx8WJ/4403MJvN3HbbbQ5jXRpBIfA8GmwW9hV/7W4xmkQCoYwJvA6FUsHgIT3Y9HHLybRdyY/fn2PsRMfEx00pYwKBoPNpc5Slp9JS9InA9RTXF7C7cKu7xWgGiXE9ZuCjFH4PAu/CarXx37WHyPj8BKUlnZtKRqlS8PKb0whupnqIwPPorChLQefi7LkRr0KCdhGkDfXgouIy2ZXdI7+T4OpCqVQw9c5BvPzWNEaM6tmpYxkMGgKDxEuLQOApCIVM0C4UkpJRkbcwKmKSRypmxfUF7hZBIGg3KrWSXz1xPQsXjWXanYNIua6Hy8eoKK/nX2/sppsskggEXo9QyATtRiEpMGqD8fXAVBFqRecVvxUIugJJkkhOieIXswbz2O9vIChY75J+R4/rTdqYXgDs+SYbixtyngk8l6IqExsO5rNm/1k2HMynqKprAkwELkh7Ibi6sdoaKPLAUkIxho7VCBUIPAmFUkH/QRF8+9XpDvVz55xrmfSLJOrrLCgkGDYyDo1WPAYEcCS/krd3n+HrU8VYL6nKoFRIjE4I4b4RcQyI9LyX7+6EsJAJOoQkSWg9zHm+j3EQUb493S2GQOBSAoM6ZiHz89dy8639AfDRqZn7+EiuGer6pVCB9/HV8fP8cvX3fHXivIMyBmC1yXx1onF/xonzLh978eLFSJLk8ImIiLDvX7duHenp6YSEhCBJkr0o+KWYTCYeffRRQkJC8PX15dZbbyU319FQ8Pzzz5OWloZerycgIKBJWfbu3cvYsWMJCAggMDCQCRMmOIx37NgxbrzxRsLDw/Hx8aFXr1788Y9/xGJxTRJnoZAJOoRCUnqUNSrO0Je+xtYrPQgE3kaPuIB2HxsW4YfVKlNX1zXZ/wXew5H8Sp7ecBizteXi4marjafWH+ZIfqXLZUhKSiI/P9/+OXjwoH1fTU0NI0eOZNmyZc0eP3/+fD7++GPWrFnDjh07qK6uZvLkyVitF5fjzWYzt99+Ow8//HCTfVRVVZGenk5sbCx79uxhx44d+Pv7k56eble41Go199xzD59//jnHjh3j9ddfZ/ny5SxatMglv4OwVQs6hNXWQH5ttrvFwEepp19ACtG+8SKLuKBbEtXD2K7jAoJ0vPjGVHuRcIHgUt7efaZVZewCZquNt/ec4eVpyS6VQaVSOVjFLmX27NkAZGdnN7m/oqKCFStW8O677zJu3DgA3nvvPWJiYti2bRvp6ekAPPvsswCsXLmyyX6OHTtGWVkZzz33nL0u9qJFixg0aBA5OTkkJCTQq1cvevXqZT8mLi6OjIwMvvnmmzbPuSmEhUzQbszWevYXf02VpcJtMhg1wQwNHcNN0dPoYegllDFBtyUswoDUDqWqwWITypigSYqqTHx9srhNx3x9stjljv4nTpwgKiqK+Ph4Zs6cyenTzvtK7t+/H4vFwoQJE+zboqKiGDhwIDt37nS6n8TEREJCQlixYgVms5m6ujpWrFhBUlIScXFxTR5z8uRJNm/ezA033OD0OC0hFDJBu8nIW09R3TmX9xuoDXW67YjwcUToY1BISpfLIRB4EvnnKpFtbUtRMX5yP1795/ROkkjg7ezJLsXaxrQnVpvMd2dKXSbD8OHDeeedd9iyZQvLly+noKCAtLQ0SkpKnDq+oKAAjUZDYGCgw/bw8HB7KUZn8PPzIyMjg/feew+dTofBYGDLli1s2rQJlcpxMTEtLQ0fHx/69OnDqFGjeO6555wepyWEQiZoN0lBw9qkPDWHXuXHiLBxjIm6lX4B15AU6Fy/SkmFWqHp8PgCgTdw+oRzD6hLqa6stxcHFwgup8bc0K7jqk3tO64pJk6cyIwZM0hOTmbcuHFs3LgRgFWrVnWoX1mW27RiUldXx/3338/IkSPZvXs33377LUlJSUyaNIm6ujqHtv/+97/5/vvvWb16NRs3buSVV17pkKwXEFeqoN1E+8YTqY9je94Gahra7+jZ2ziQEF3kz/9v9E1I8E9i3/mMJtsHacPo6dePOmtNu8cUCLyNsRP7cjgzj++/cz7NzK6vsxkxOl5EUwqaxFfTPhXA0IlKvq+vL8nJyZw4ccKp9hEREZjNZsrKyhysZEVFRaSlpTk97urVq8nOzmbXrl32eturV68mMDCQTz/9lJkzZ9rbXvAxGzBgAFarlQcffJAFCxagVHZspUZYyAQdQiEpiPXr065j4wx9SQm5niBtKDbZhk2+6FgaruuBRqG94hi9ysDQ0DFE+caR4D+g3XILBN6GJEnM++1oHvrNSO6bN4Knl6YTEdV6Xqi172WKbPyCJhneMwhlG/0LlQqJ6+KCOkmixhQWR48eJTIy0qn2Q4YMQa1Ws3XrxdrK+fn5HDp0qE0KWW1tLQqFwsGqduG7zdZ80IMsy1gsFpdcY8JCJugwwdrwdh13riYLjdIHP3UAX5xbh0220suvP72NyUiSxLWho68oYD44OA2N8kpFTSC4GlCplaTdcDHKK+maSAryWrZO5+dWUFRQTXikX2eLJ/Aywvy0jE4I4as25Bcb3TuEMD/X3YMXLlzIlClTiI2NpaioiCVLllBZWcmcOXMAKC0tJScnh7y8PKAxGhIaLWMREREYjUYeeOABFixYQHBwMEFBQSxcuNC+BHqBnJwce19Wq9WeX6x3794YDAbGjx/Pb3/7W+bNm8ejjz6KzWZj2bJlqFQqbrzxRgDef/991Go1ycnJaLVa9u/fz5NPPsmdd955hZ9ZexAKmaDD+KmNBGpDKTO1flFrlTpM1sb1+Eh9LL39k/gy7xP7tmMVP1BnrWFg0HBCfCLoaxzM8YofAIjzSyTYp33Kn0DQHZk551qyT5Zw6viVkXL+Rh/SxvRi5I29hDImaJb7RsTx7ekSp1JfaFUK7hvedMRhe8nNzWXWrFkUFxcTGhrKiBEj2L17tz2ycf369dx333329heWDhctWsTixYsBeO2111CpVNxxxx3U1dUxduxYVq5c6bCE+Mwzzzj4paWkpADw1VdfMWbMGPr168eGDRt49tlnSU1NRaFQkJKSwubNm+3WOpVKxYsvvsjx48eRZZm4uDjmzZvHb37zG5f8FpLcTWzZlZWVGI1GKioq8PcX5R26GpO1jq25a1ts46vy57qwmzhZcZCzNaeI8U0g2CeCzJJvr2g7JPQGIvWx2GQrW3PXIssyN0X/QljHBILL2LMjmzdeccyDpPVR8cpb0/AP8KwqGoKO0dJzrr6+nqysLOLj4/Hx8WlTvxknzvPU+paTw2qUCl64NYkxfToeyHW14ey5ERYygUvQKnUMCk7laNn3WGxX5qiJ1Mdxbcj1SJKCxMCUxn8DBlPbUN1kfxWmEiL1sSgkJXqVgWCfCKGMCQRNEBbhaP3qNzCcX8wajFpEVwqcZEyfUP5517W8vecMX59sopZl7xDuGy5qWXY24ooVuIxYQ2+i9HFk5K2n3lpr3+6r8mNQ8AgkqTGGxEepY1DwCKBRkYvUx5Ffe8ahLz9NgP3/Ybpoevoldv4EBAIvJCzCj6AQPaXFjdfcT4cKWfr05ygUEuNuSeTuB4a5WUKBNzAg0p+XpyVTVGXiuzOlVJsaMGhVXBcX5FKfMUHzCIVM4FJUCjW+Kj+7QiYhcU3I9S3mC+vlP8BBIdOrDEToY+3fEwOu6TR5BQJv5++v7bArY9DoO3bnnGs5lJnHwMFRbpRM4I2E+WmZPNC5CEeBaxEKmcDlJAcPZ//57VRZKhgYNJxAbUiL7Y2aIBKNgzlXk4VOZWBg0HUoReZ9gcApfjFrMIcy87BaG5eZEpPCuf6mBK6/KcHNkgkEgrYgFDKByzGojYyOnIINm1OKlUJS0CdgEH0CBnWBdAJB9yK+dzAz7x3C+yv2AY01LwUCgfchFDJBpyBJEkqElUsg6ArGT+5HYHCjH9mwka5NSyAQCLoGoZAJBAKBlyNJEsPShCImEHgzonSSQCAQCAQCgZsRFjKBQCAQCAQAFJfXceCn89TWW9D7qEnpF0qISDDcJQiFTCAQCASCq5zjOWX8e8sJ9hwquCIx7PCBEdyZ3oe+sYFulLD7I5YsBQKBQCC4ivn2hzwWvraDnT/mOyhjAFabzM4f8xv3/5Dv8rEXL16MJEkOn4iICPv+devWkZ6eTkhICJIk2YuCX4rJZOLRRx8lJCQEX19fbr31VnJzcx3aPP/886SlpaHX6wkICGhSlr179zJ27FgCAgIIDAxkwoQJTY4HcPLkSfz8/Jrtqz0IhUwgEAgEgquU4zllvLhyP5aGlouLWxpsLFu5j+M5ZS6XISkpifz8fPvn4MGD9n01NTWMHDmSZcuWNXv8/Pnz+fjjj1mzZg07duygurqayZMnY7Va7W3MZjO33347Dz/8cJN9VFVVkZ6eTmxsLHv27GHHjh34+/uTnp6OxWJxaGuxWJg1axajRo3q4MwdEUuWAoFAIBBcpfx7y4lWlbELWBps/OfzE/zxl9e5VAaVSuVgFbuU2bNnA5Cdnd3k/oqKClasWMG7777LuHHjAHjvvfeIiYlh27ZtpKenA/Dss88CsHLlyib7OXbsGGVlZTz33HPExMQAsGjRIgYNGkROTg4JCRcTLf/xj3+kX79+jB07lp07d7Z5vs0hLGQCgUAgEFyFFJfXsftQQZuO2X2wgOLyOpfKceLECaKiooiPj2fmzJmcPn3a6WP379+PxWJhwoQJ9m1RUVEMHDiwTcpSYmIiISEhrFixArPZTF1dHStWrCApKYm4uIspZb788ks+/PBD/va3vzndt7MIhUwgEAgEgquQAz+dx3aZz1hrWG0yB46dd5kMw4cP55133mHLli0sX76cgoIC0tLSKCkpcer4goICNBoNgYGOAQfh4eEUFDivbPr5+ZGRkcF7772HTqfDYDCwZcsWNm3ahErVuJhYUlLCvffey8qVK/H393d+kk4iFDKBQCAQCK5CaustrTdq8rgGl8kwceJEZsyYQXJyMuPGjWPjxo0ArFq1qkP9yrKMJElOt6+rq+P+++9n5MiR7N69m2+//ZakpCQmTZpEXV2jRXDu3LncddddjB49ukOyNYdQyAQCgUAguArR+6jbeVznuZ/7+vqSnJzMiRMnnGofERGB2WymrMwx2KCoqIjw8HCnx129ejXZ2dm8/fbbDBs2jBEjRrB69WqysrL49NNPgcblyldeeQWVSoVKpeKBBx6goqIClUrFv/71L+cn2QxCIRMIBAKB4CokpV8oSoXzViRozEuWkhjaSRI1prA4evQokZGRTrUfMmQIarWarVu32rfl5+dz6NAh0tLSnB63trYWhULhYFW78N1mawx62LVrF5mZmfbPc889h5+fH5mZmfziF79weqzmEFGWAoFAIBBchYQE6Bg+MIKdPzqfX2xEcoRLM/cvXLiQKVOmEBsbS1FREUuWLKGyspI5c+YAUFpaSk5ODnl5eUBjNCQ0WsYiIiIwGo088MADLFiwgODgYIKCgli4cKF9CfQCOTk59r6sVqs9v1jv3r0xGAyMHz+e3/72t8ybN49HH30Um83GsmXLUKlU3HjjjQD079/fQfZ9+/ahUCgYOHCgS34LYSETCAQCgeAq5c70PqhVzqkCGrWCOyb0cen4ubm5zJo1i8TERKZPn45Go2H37t32yMb169eTkpLCLbfcAsDMmTNJSUnhrbfesvfx2muvMW3aNO644w5GjhyJXq9nw4YNKJVKe5tnnnmGlJQUFi1aRHV1NSkpKaSkpLBv3z4A+vXrx4YNG/jxxx9JTU1l1KhR5OXlsXnzZqetdR1FkmW5bSEWHkplZSVGo5GKiopOiX4QCAQCgcCdtPScq6+vJysri/j4eHx8fNrU784f8lm2cl+L+cjUKgV/uHcoaYO7RjnpTjh7brrNkuUFvbKystLNkggEAoFA4HouPN9cbUdJGxzJK7+5nv98foLdB6+sZTkiOYI7Johalp1Nt1HIqqqqAOwZdgUCgUAg6I5UVVVhNBpd2mff2ED++MvrKC6v48Cx89TWN6D3UZGSGOpSnzFB83QbhSwqKoqzZ8/i5+fXptwj0PjWERMTw9mzZ7vVcmd3nFd3nBOIeXkT3XFOIOblDciyTFVVFVFRUZ02RkiAjvHDYzutf0HzdBuFTKFQ0KNHjw714e/v7/UXbFN0x3l1xzmBmJc30R3nBGJeno6rLWMCz0FEWQoEAoFAIBC4GaGQCQQCgUAgELgZoZABWq2WRYsWodVq3S2KS+mO8+qOcwIxL2+iO84JxLwEAnfTbfKQCQQCgUBwtdKRPGSCzuWqy0MmEAgEAoGgY5SW1HI4M5+6OjM6nYakayIJCta7W6yrAqGQCQQCgUBwlZN1soQNaw+SuTcXq/WSxLBKiWuG9WDKbcnE9w52o4TdH+FDJhAIBALBVcy+3Tk8/+Rm9u8+66CMAVitMvt3n/15f47Lx168eDGSJDl8IiIi7PvXrVtHeno6ISEhSJJkLwp+gdLSUh599FESExPR6/XExsby2GOPUVFR4dCurKyM2bNnYzQaMRqNzJ49m/Lycoc2e/fuZezYsQQEBBAYGMiECRMcxquvr+fee+8lOTkZlUrFtGnTXPpbCIVMIBAIBIKrlKyTJbz1v99gsTRfxxLAYrHx5v9+Q9bJEpfLkJSURH5+vv1z8OBB+76amhpGjhzJsmXLmjw2Ly+PvLw8XnnlFQ4ePMjKlSvZvHkzDzzwgEO7u+66i8zMTDZv3szmzZvJzMxk9uzZ9v1VVVWkp6cTGxvLnj172LFjB/7+/qSnp2OxWACwWq3odDoee+wxxo0b5/LfwasUsq+//popU6YQFRWFJEl88sknDvtlWWbx4sVERUWh0+kYM2YMhw8fdmjz0EMPkZCQgE6nIzQ0lKlTp/LTTz+1OvYbb7xhd8gbMmQI33zzTZvH9rR5LV26lGHDhuHn50dYWBjTpk3j2LFjDm3uvffeK95eRowY4dHzau2Ny9mxPWlOPXv2vGJOkiQxb948ext3n6tL206cOLHJfpqis64td83JG66r9syrM68rd86rs68tT2fD2oOtKmMXsFhs/HftIZfLoFKpiIiIsH9CQ0Pt+2bPns0zzzzTrAI0cOBAPvroI6ZMmUJCQgI33XQTzz//PBs2bKChoQGAo0ePsnnzZv75z3+SmppKamoqy5cv57///a/92jx27BhlZWU899xzJCYmkpSUxKJFiygqKiInp9Ey6Ovry5tvvsncuXOv+Nt3BV6lkNXU1DB48GD++te/Nrn/pZde4tVXX+Wvf/0re/fuJSIigvHjx9vrXAIMGTKEt99+m6NHj7JlyxZkWWbChAlYrdZmx/33v//N/Pnzefrppzlw4ACjRo1i4sSJ9pPk7NieNq/t27czb948du/ezdatW2loaGDChAnU1NQ4tLv55psd3l42bdrU6pzcOS9o+Y3L2bE9aU579+51mM/WrVsBuP322x3aufNcXeD11193unxZZ15b7pqTN1xX7ZkXdN515c55dfa15cmUltRy4LvcNh1zYO9ZSktqXSrHiRMniIqKIj4+npkzZ3L69OkO9VdRUYG/vz8qVaOb/K5duzAajQwfPtzeZsSIERiNRnbu3AlAYmIiISEhrFixArPZTF1dHStWrCApKYm4uLgOyeM0spcCyB9//LH9u81mkyMiIuRly5bZt9XX18tGo1F+6623mu3nhx9+kAH55MmTzba57rrr5F/96lcO2/r16yf/4Q9/6NDY7p7X5RQVFcmAvH37dvu2OXPmyFOnTm3THJqiK+e1aNEiefDgwc3ud9X5cue5evzxx+WEhATZZrPZt3nCucrMzJR79Ogh5+fnX9FPU3TVtdWVc7ocT72u2jqvrrquunpel9OZ11ZnUldXJx85ckSuq6tz+pivt52U75n6Tps/33zh/L2qNTZt2iSvXbtW/vHHH+WtW7fKN9xwgxweHi4XFxc7tMvKypIB+cCBAy32V1xcLMfGxspPP/20fdvzzz8v9+nT54q2ffr0kV944QX790OHDskJCQmyQqGQFQqF3K9fP/nMmTNNjtOWvwlnz41XWchaIisri4KCAiZMmGDfptVqueGGG+wa8OXU1NTw9ttvEx8fT0xMTJNtzGYz+/fvd+gXYMKECfZ+2zO2u+fVFBecIIOCghy2Z2RkEBYWRt++fZk7dy5FRUXtmIkjnT2vlt64Out8ddW5MpvNvPfee9x///1XWAHcea5qa2uZNWsWf/3rX50y57vz2uqsOTWFJ15X7Z2XO66rrpjXBbr62nI3dXXm9h1Xa3GZDBMnTmTGjBkkJyczbtw4Nm7cCMCqVava3FdlZSW33HILAwYMYNGiRQ77mrKYyrJs315XV8f999/PyJEj2b17N99++y1JSUlMmjSJurq6dsys7XQbhaygoACA8PBwh+3h4eH2fRd44403MBgMGAwGNm/ezNatW9FoNE32W1xcjNVqbbHftozdVjprXpcjyzJPPPEE119/PQMHDrRvnzhxIu+//z5ffvkl//u//8vevXu56aabMJlMHjuv4cOH884777BlyxaWL19OQUEBaWlplJSUtHlsT5nTpXzyySeUl5dz7733Omx397n6zW9+Q1paGlOnTnWqX3deW501p8vx1OuqPfNy13XVlr47er66+tpyNzqdc/ecK47Tq10syUV8fX1JTk7mxIkTbTquqqqKm2++GYPBwMcff4xafVHGiIgICgsLrzjm/Pnz9r+p1atXk52dzdtvv82wYcMYMWIEq1evJisri08//bRjk3KSbpeH7HIt+FIN+AJ3330348ePJz8/n1deeYU77riDb7/9tsUMus7060yb9tJZ87rAI488wo8//siOHTsctt955532/w8cOJChQ4cSFxfHxo0bmT59egdm1EhnzGvixIn2/ycnJ5OamkpCQgKrVq3iiSeeaNPY7aGzz9WKFSuYOHEiUVFRDtvdea7Wr1/Pl19+yYEDB1zab1vatIfOmtMFPPG6au+83H1dtda3K86Xu64td5F0TSRKpXRFqouWUColBgyO7DSZTCYTR48eZdSoUU4fU1lZSXp6OlqtlvXr119xH01NTaWiooLvvvuO6667DoA9e/ZQUVFBWloa0GhdVSgUDn9jF77bbM4FPXSUbmMhu2CevvxNrKio6Iq3KqPRSJ8+fRg9ejRr167lp59+4uOPP26y35CQEJRKZYv9tmXsttJZ87qURx99lPXr1/PVV1/Ro0ePIqgRDAAABbtJREFUFttGRkYSFxfX5reXy+mKeV3g8jeuzjpfXTGnM2fOsG3bNn75y1+22rYrz9WXX37JqVOnCAgIQKVS2Z1pZ8yYwZgxY5rs153XVmfN6VI89brq6Lwu0FXXlbN9d3Re7ri23E1QsJ5rhrX8t3k5KcNiXJq5f+HChWzfvp2srCz27NnDbbfdRmVlJXPmzAEa84xlZmZy5MgRoDEaMjMz0/63UFVVZQ+aWbFiBZWVlRQUFFBQUGAPlOrfvz8333wzc+fOZffu3ezevZu5c+cyefJkEhMTARg/fjxlZWXMmzePo0ePcvjwYe677z5UKhU33nijXd4jR46QmZlJaWkpFRUVZGZmXpEbrb10G4UsPj6eiIgIe4QMNPoDbN++3a4BN4csy82anjUaDUOGDHHoF2Dr1q32fjsydmt01rwu7H/kkUdYt24dX375JfHx8a3KU1JSwtmzZ4mM7NgbUmfO63IuvHFdkLmzzldXzOntt98mLCyMW265pdW2XXmu/vCHP/Djjz/ab04XblCvvfYab7/9dpP9uvPa6qw5gedfV+2d1+V01XXVVfNyx7XlCUy5LRm12jlVQK1RMvm2ga03bAO5ubnMmjWLxMREpk+fjkajYffu3fbIxvXr15OSkmI/LzNnziQlJYW33noLgP3797Nnzx4OHjxI7969iYyMtH/Onj1rH+f9998nOTmZCRMmMGHCBAYNGsS7775r39+vXz82bNjAjz/+SGpqKqNGjSIvL4/Nmzc7nOdJkyaRkpLChg0byMjIICUlhZSUFNf8GE6FCHgIVVVV8oEDB+QDBw7IgPzqq6/KBw4csEdBLFu2TDYajfK6devkgwcPyrNmzZIjIyPlyspKWZZl+dSpU/ILL7wg79u3Tz5z5oy8c+dOeerUqXJQUJBcWFhoH+emm26S/9//+3/272vWrJHVarW8YsUK+ciRI/L8+fNlX19fOTs7296mtbE9cV4PP/ywbDQa5YyMDDk/P9/+qa2ttcu1YMECeefOnXJWVpb81VdfyampqXJ0dLRHz2vBggVyRkaGfPr0aXn37t3y5MmTZT8/P5ecL3fNSZZl2Wq1yrGxsfLvf//7JuVy57lqCpqIcOvKa8tdc/L066q98+rM68qd85Llzr22uor2RFleYN+uM/IDt73XYmTlA7e9J+/b1XTEoaBlnD03XqWQffXVVzJwxWfOnDmyLDeGRi9atEiOiIiQtVqtPHr0aPngwYP248+dOydPnDhRDgsLk9VqtdyjRw/5rrvukn/66SeHceLi4uRFixY5bPvb3/4mx8XFyRqNRr722msdQtidGdsT59XUmID89ttvy7Isy7W1tfKECRPk0NBQWa1Wy7GxsfKcOXPknJwcj57XnXfeKUdGRspqtVqOioqSp0+fLh8+fNjhmPaeL3f+DW7ZskUG5GPHjl0hl7vPVVM09TDsymvLXXPy9OuqvfPqzOvKnfOS5c69trqKjihksizLp08Uy/+3NEO+b/q7DorYfdPflf9vaYZ8+kRx650ImsTZcyPJsuy8N59AIBAIBAKPo76+nqysLHvVi/ZSWlLLkR/yqau1oNOrGTA40qU+Y1cjzp6bbhdlKRAIBAKBoH0EBeu5/qYEd4txVdJtnPoFAoFAIBAIvBWhkAkEAoFA0E0QXkieh7PnRChkAoFAIBB4OUqlEmhMByLwLGprG4uxX1o9oCmED5lAIBAIBF6OSqVCr9dz/vx51Go1CoWwt7gbWZapra2lqKiIgIAAu9LcHCLKUiAQCASCboDZbCYrK6vLSv0InCMgIICIiIhWS4gJhUwgEAgEgm6CzWYTy5YehFqtbtUydgGhkAkEAoFAIBC4GbHILBAIBAKBQOBmhEImEAgEAoFA4GaEQiYQCAQCgUDgZoRCJhAIBAKBQOBmhEImEAgEAoFA4GaEQiYQCAQCgUDgZoRCJhAIBAKBQOBm/j+4mSE8Cw6hpwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>DISTNAME</th>\n",
       "      <th>DISTCODE</th>\n",
       "      <th>CITYCODE</th>\n",
       "      <th>PROVCODE</th>\n",
       "      <th>CITYNAME</th>\n",
       "      <th>PROVNAME</th>\n",
       "      <th>SHAPE_LENG</th>\n",
       "      <th>Shape_Le_1</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>简阳市</td>\n",
       "      <td>512081</td>\n",
       "      <td>512000</td>\n",
       "      <td>510000</td>\n",
       "      <td>资阳市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>2.894016</td>\n",
       "      <td>2.894016</td>\n",
       "      <td>0.208108</td>\n",
       "      <td>POLYGON ((104.87300 30.51160, 104.87300 30.511...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>锦江区</td>\n",
       "      <td>510104</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.543100</td>\n",
       "      <td>0.543100</td>\n",
       "      <td>0.005721</td>\n",
       "      <td>POLYGON ((104.13780 30.62028, 104.13918 30.620...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>青羊区</td>\n",
       "      <td>510105</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.638742</td>\n",
       "      <td>0.638740</td>\n",
       "      <td>0.006232</td>\n",
       "      <td>POLYGON ((103.94156 30.72649, 103.94223 30.725...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>金牛区</td>\n",
       "      <td>510106</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.076539</td>\n",
       "      <td>1.076541</td>\n",
       "      <td>0.010065</td>\n",
       "      <td>POLYGON ((104.13695 30.74670, 104.13652 30.746...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>成华区</td>\n",
       "      <td>510108</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.768822</td>\n",
       "      <td>0.768824</td>\n",
       "      <td>0.010192</td>\n",
       "      <td>POLYGON ((104.13695 30.74670, 104.13795 30.744...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>龙泉驿区</td>\n",
       "      <td>510112</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.335728</td>\n",
       "      <td>1.335729</td>\n",
       "      <td>0.052623</td>\n",
       "      <td>POLYGON ((104.43712 30.66993, 104.43719 30.669...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>青白江区</td>\n",
       "      <td>510113</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.348517</td>\n",
       "      <td>1.348519</td>\n",
       "      <td>0.036493</td>\n",
       "      <td>POLYGON ((104.34159 30.90460, 104.34202 30.904...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>新都区</td>\n",
       "      <td>510114</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.697892</td>\n",
       "      <td>1.697894</td>\n",
       "      <td>0.045477</td>\n",
       "      <td>POLYGON ((104.14722 30.91626, 104.14741 30.916...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>温江区</td>\n",
       "      <td>510115</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.993996</td>\n",
       "      <td>0.993995</td>\n",
       "      <td>0.026206</td>\n",
       "      <td>POLYGON ((103.71485 30.86386, 103.71585 30.862...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>金堂县</td>\n",
       "      <td>510121</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>2.548990</td>\n",
       "      <td>2.548992</td>\n",
       "      <td>0.109013</td>\n",
       "      <td>POLYGON ((104.49533 30.93919, 104.49558 30.939...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>郫都区</td>\n",
       "      <td>510124</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.217965</td>\n",
       "      <td>1.217965</td>\n",
       "      <td>0.041267</td>\n",
       "      <td>POLYGON ((103.77771 30.96121, 103.77911 30.960...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>大邑县</td>\n",
       "      <td>510129</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>2.428597</td>\n",
       "      <td>2.428597</td>\n",
       "      <td>0.113637</td>\n",
       "      <td>POLYGON ((103.11740 30.79702, 103.11741 30.796...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>蒲江县</td>\n",
       "      <td>510131</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.452034</td>\n",
       "      <td>1.452033</td>\n",
       "      <td>0.054485</td>\n",
       "      <td>POLYGON ((103.68133 30.27418, 103.68085 30.274...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>新津县</td>\n",
       "      <td>510132</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.873948</td>\n",
       "      <td>0.873948</td>\n",
       "      <td>0.031103</td>\n",
       "      <td>POLYGON ((103.91963 30.36274, 103.91919 30.362...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>都江堰市</td>\n",
       "      <td>510181</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>2.034713</td>\n",
       "      <td>2.034714</td>\n",
       "      <td>0.113709</td>\n",
       "      <td>POLYGON ((103.77771 30.96121, 103.77630 30.961...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>彭州市</td>\n",
       "      <td>510182</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>2.128521</td>\n",
       "      <td>2.128521</td>\n",
       "      <td>0.134319</td>\n",
       "      <td>POLYGON ((104.11761 31.03188, 104.11743 31.031...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>邛崃市</td>\n",
       "      <td>510183</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>2.397509</td>\n",
       "      <td>2.397510</td>\n",
       "      <td>0.129317</td>\n",
       "      <td>POLYGON ((103.70562 30.43709, 103.70434 30.436...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>崇州市</td>\n",
       "      <td>510184</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>2.193338</td>\n",
       "      <td>2.193339</td>\n",
       "      <td>0.102694</td>\n",
       "      <td>POLYGON ((103.43061 30.88060, 103.42939 30.878...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>武侯区</td>\n",
       "      <td>510107</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.715112</td>\n",
       "      <td>0.569811</td>\n",
       "      <td>0.008688</td>\n",
       "      <td>POLYGON ((104.07713 30.59229, 104.00922 30.592...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>高新区</td>\n",
       "      <td>510107</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.715112</td>\n",
       "      <td>0.291560</td>\n",
       "      <td>0.002789</td>\n",
       "      <td>POLYGON ((104.07713 30.59229, 104.07675 30.591...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>天府新区</td>\n",
       "      <td>510122</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.984275</td>\n",
       "      <td>1.167820</td>\n",
       "      <td>0.057835</td>\n",
       "      <td>POLYGON ((103.97310 30.30938, 103.97984 30.317...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>双流区</td>\n",
       "      <td>510122</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.984275</td>\n",
       "      <td>1.296602</td>\n",
       "      <td>0.042520</td>\n",
       "      <td>POLYGON ((104.04370 30.53334, 104.04471 30.532...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    OBJECTID DISTNAME DISTCODE CITYCODE PROVCODE CITYNAME PROVNAME  \\\n",
       "0          1      简阳市   512081   512000   510000      资阳市      四川省   \n",
       "1          2      锦江区   510104   510100   510000      成都市      四川省   \n",
       "2          3      青羊区   510105   510100   510000      成都市      四川省   \n",
       "3          4      金牛区   510106   510100   510000      成都市      四川省   \n",
       "4          5      成华区   510108   510100   510000      成都市      四川省   \n",
       "5          6     龙泉驿区   510112   510100   510000      成都市      四川省   \n",
       "6          7     青白江区   510113   510100   510000      成都市      四川省   \n",
       "7          8      新都区   510114   510100   510000      成都市      四川省   \n",
       "8          9      温江区   510115   510100   510000      成都市      四川省   \n",
       "9         10      金堂县   510121   510100   510000      成都市      四川省   \n",
       "10        11      郫都区   510124   510100   510000      成都市      四川省   \n",
       "11        12      大邑县   510129   510100   510000      成都市      四川省   \n",
       "12        13      蒲江县   510131   510100   510000      成都市      四川省   \n",
       "13        14      新津县   510132   510100   510000      成都市      四川省   \n",
       "14        15     都江堰市   510181   510100   510000      成都市      四川省   \n",
       "15        16      彭州市   510182   510100   510000      成都市      四川省   \n",
       "16        17      邛崃市   510183   510100   510000      成都市      四川省   \n",
       "17        18      崇州市   510184   510100   510000      成都市      四川省   \n",
       "18        19      武侯区   510107   510100   510000      成都市      四川省   \n",
       "19        20      高新区   510107   510100   510000      成都市      四川省   \n",
       "20        21     天府新区   510122   510100   510000      成都市      四川省   \n",
       "21        22      双流区   510122   510100   510000      成都市      四川省   \n",
       "\n",
       "    SHAPE_LENG  Shape_Le_1  Shape_Area  \\\n",
       "0     2.894016    2.894016    0.208108   \n",
       "1     0.543100    0.543100    0.005721   \n",
       "2     0.638742    0.638740    0.006232   \n",
       "3     1.076539    1.076541    0.010065   \n",
       "4     0.768822    0.768824    0.010192   \n",
       "5     1.335728    1.335729    0.052623   \n",
       "6     1.348517    1.348519    0.036493   \n",
       "7     1.697892    1.697894    0.045477   \n",
       "8     0.993996    0.993995    0.026206   \n",
       "9     2.548990    2.548992    0.109013   \n",
       "10    1.217965    1.217965    0.041267   \n",
       "11    2.428597    2.428597    0.113637   \n",
       "12    1.452034    1.452033    0.054485   \n",
       "13    0.873948    0.873948    0.031103   \n",
       "14    2.034713    2.034714    0.113709   \n",
       "15    2.128521    2.128521    0.134319   \n",
       "16    2.397509    2.397510    0.129317   \n",
       "17    2.193338    2.193339    0.102694   \n",
       "18    0.715112    0.569811    0.008688   \n",
       "19    0.715112    0.291560    0.002789   \n",
       "20    1.984275    1.167820    0.057835   \n",
       "21    1.984275    1.296602    0.042520   \n",
       "\n",
       "                                             geometry  \n",
       "0   POLYGON ((104.87300 30.51160, 104.87300 30.511...  \n",
       "1   POLYGON ((104.13780 30.62028, 104.13918 30.620...  \n",
       "2   POLYGON ((103.94156 30.72649, 103.94223 30.725...  \n",
       "3   POLYGON ((104.13695 30.74670, 104.13652 30.746...  \n",
       "4   POLYGON ((104.13695 30.74670, 104.13795 30.744...  \n",
       "5   POLYGON ((104.43712 30.66993, 104.43719 30.669...  \n",
       "6   POLYGON ((104.34159 30.90460, 104.34202 30.904...  \n",
       "7   POLYGON ((104.14722 30.91626, 104.14741 30.916...  \n",
       "8   POLYGON ((103.71485 30.86386, 103.71585 30.862...  \n",
       "9   POLYGON ((104.49533 30.93919, 104.49558 30.939...  \n",
       "10  POLYGON ((103.77771 30.96121, 103.77911 30.960...  \n",
       "11  POLYGON ((103.11740 30.79702, 103.11741 30.796...  \n",
       "12  POLYGON ((103.68133 30.27418, 103.68085 30.274...  \n",
       "13  POLYGON ((103.91963 30.36274, 103.91919 30.362...  \n",
       "14  POLYGON ((103.77771 30.96121, 103.77630 30.961...  \n",
       "15  POLYGON ((104.11761 31.03188, 104.11743 31.031...  \n",
       "16  POLYGON ((103.70562 30.43709, 103.70434 30.436...  \n",
       "17  POLYGON ((103.43061 30.88060, 103.42939 30.878...  \n",
       "18  POLYGON ((104.07713 30.59229, 104.00922 30.592...  \n",
       "19  POLYGON ((104.07713 30.59229, 104.07675 30.591...  \n",
       "20  POLYGON ((103.97310 30.30938, 103.97984 30.317...  \n",
       "21  POLYGON ((104.04370 30.53334, 104.04471 30.532...  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cddistrict = gpd.read_file('./data/chengdu.shp')\n",
    "cddistrict.plot(column='DISTCODE',categorical=True,cmap='Spectral',legend=True,legend_kwds={'loc': 'center left', 'bbox_to_anchor':(1,0.5)})\n",
    "plt.show()\n",
    "cddistrict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "总共找到12个与成都是相交的县区\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>DISTNAME</th>\n",
       "      <th>DISTCODE</th>\n",
       "      <th>CITYCODE</th>\n",
       "      <th>PROVCODE</th>\n",
       "      <th>CITYNAME</th>\n",
       "      <th>PROVNAME</th>\n",
       "      <th>SHAPE_LENG</th>\n",
       "      <th>Shape_Le_1</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>锦江区</td>\n",
       "      <td>510104</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.543100</td>\n",
       "      <td>0.543100</td>\n",
       "      <td>0.005721</td>\n",
       "      <td>POLYGON ((104.13780 30.62028, 104.13918 30.620...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>青羊区</td>\n",
       "      <td>510105</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.638742</td>\n",
       "      <td>0.638740</td>\n",
       "      <td>0.006232</td>\n",
       "      <td>POLYGON ((103.94156 30.72649, 103.94223 30.725...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>金牛区</td>\n",
       "      <td>510106</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.076539</td>\n",
       "      <td>1.076541</td>\n",
       "      <td>0.010065</td>\n",
       "      <td>POLYGON ((104.13695 30.74670, 104.13652 30.746...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>成华区</td>\n",
       "      <td>510108</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.768822</td>\n",
       "      <td>0.768824</td>\n",
       "      <td>0.010192</td>\n",
       "      <td>POLYGON ((104.13695 30.74670, 104.13795 30.744...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>龙泉驿区</td>\n",
       "      <td>510112</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.335728</td>\n",
       "      <td>1.335729</td>\n",
       "      <td>0.052623</td>\n",
       "      <td>POLYGON ((104.43712 30.66993, 104.43719 30.669...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>新都区</td>\n",
       "      <td>510114</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.697892</td>\n",
       "      <td>1.697894</td>\n",
       "      <td>0.045477</td>\n",
       "      <td>POLYGON ((104.14722 30.91626, 104.14741 30.916...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>温江区</td>\n",
       "      <td>510115</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.993996</td>\n",
       "      <td>0.993995</td>\n",
       "      <td>0.026206</td>\n",
       "      <td>POLYGON ((103.71485 30.86386, 103.71585 30.862...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>郫都区</td>\n",
       "      <td>510124</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.217965</td>\n",
       "      <td>1.217965</td>\n",
       "      <td>0.041267</td>\n",
       "      <td>POLYGON ((103.77771 30.96121, 103.77911 30.960...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>武侯区</td>\n",
       "      <td>510107</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.715112</td>\n",
       "      <td>0.569811</td>\n",
       "      <td>0.008688</td>\n",
       "      <td>POLYGON ((104.07713 30.59229, 104.00922 30.592...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>高新区</td>\n",
       "      <td>510107</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>0.715112</td>\n",
       "      <td>0.291560</td>\n",
       "      <td>0.002789</td>\n",
       "      <td>POLYGON ((104.07713 30.59229, 104.07675 30.591...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>天府新区</td>\n",
       "      <td>510122</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.984275</td>\n",
       "      <td>1.167820</td>\n",
       "      <td>0.057835</td>\n",
       "      <td>POLYGON ((103.97310 30.30938, 103.97984 30.317...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>双流区</td>\n",
       "      <td>510122</td>\n",
       "      <td>510100</td>\n",
       "      <td>510000</td>\n",
       "      <td>成都市</td>\n",
       "      <td>四川省</td>\n",
       "      <td>1.984275</td>\n",
       "      <td>1.296602</td>\n",
       "      <td>0.042520</td>\n",
       "      <td>POLYGON ((104.04370 30.53334, 104.04471 30.532...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    OBJECTID DISTNAME DISTCODE CITYCODE PROVCODE CITYNAME PROVNAME  \\\n",
       "1          2      锦江区   510104   510100   510000      成都市      四川省   \n",
       "2          3      青羊区   510105   510100   510000      成都市      四川省   \n",
       "3          4      金牛区   510106   510100   510000      成都市      四川省   \n",
       "4          5      成华区   510108   510100   510000      成都市      四川省   \n",
       "5          6     龙泉驿区   510112   510100   510000      成都市      四川省   \n",
       "7          8      新都区   510114   510100   510000      成都市      四川省   \n",
       "8          9      温江区   510115   510100   510000      成都市      四川省   \n",
       "10        11      郫都区   510124   510100   510000      成都市      四川省   \n",
       "18        19      武侯区   510107   510100   510000      成都市      四川省   \n",
       "19        20      高新区   510107   510100   510000      成都市      四川省   \n",
       "20        21     天府新区   510122   510100   510000      成都市      四川省   \n",
       "21        22      双流区   510122   510100   510000      成都市      四川省   \n",
       "\n",
       "    SHAPE_LENG  Shape_Le_1  Shape_Area  \\\n",
       "1     0.543100    0.543100    0.005721   \n",
       "2     0.638742    0.638740    0.006232   \n",
       "3     1.076539    1.076541    0.010065   \n",
       "4     0.768822    0.768824    0.010192   \n",
       "5     1.335728    1.335729    0.052623   \n",
       "7     1.697892    1.697894    0.045477   \n",
       "8     0.993996    0.993995    0.026206   \n",
       "10    1.217965    1.217965    0.041267   \n",
       "18    0.715112    0.569811    0.008688   \n",
       "19    0.715112    0.291560    0.002789   \n",
       "20    1.984275    1.167820    0.057835   \n",
       "21    1.984275    1.296602    0.042520   \n",
       "\n",
       "                                             geometry  \n",
       "1   POLYGON ((104.13780 30.62028, 104.13918 30.620...  \n",
       "2   POLYGON ((103.94156 30.72649, 103.94223 30.725...  \n",
       "3   POLYGON ((104.13695 30.74670, 104.13652 30.746...  \n",
       "4   POLYGON ((104.13695 30.74670, 104.13795 30.744...  \n",
       "5   POLYGON ((104.43712 30.66993, 104.43719 30.669...  \n",
       "7   POLYGON ((104.14722 30.91626, 104.14741 30.916...  \n",
       "8   POLYGON ((103.71485 30.86386, 103.71585 30.862...  \n",
       "10  POLYGON ((103.77771 30.96121, 103.77911 30.960...  \n",
       "18  POLYGON ((104.07713 30.59229, 104.00922 30.592...  \n",
       "19  POLYGON ((104.07713 30.59229, 104.07675 30.591...  \n",
       "20  POLYGON ((103.97310 30.30938, 103.97984 30.317...  \n",
       "21  POLYGON ((104.04370 30.53334, 104.04471 30.532...  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cdgeom = polylayer.loc[0, 'geometry']\n",
    "mask4 = cddistrict.intersects(cdgeom)\n",
    "#步骤3\n",
    "subdistriclayer=cddistrict[mask4]\n",
    "print(f'总共找到{len(subdistriclayer)}个与成都是相交的县区')\n",
    "subdistriclayer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#显示选择结果 subdistriclayer 可以看出选出了与成都市区相交的一些县区\n",
    "ax=subdistriclayer.plot(column='DISTCODE',categorical=True,cmap='Spectral',legend=True,legend_kwds={'loc': 'center left', 'bbox_to_anchor':(1,0.5)})\n",
    "polylayer.plot(ax=ax,color=(0,0,0,0.1),edgecolor=(0,0,0,1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "parkslayer.to_file('./data/parks.shp')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pygis",
   "language": "python",
   "name": "pygis"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
